We connect enterprise systems with agentic AI, automating operational decisions, eliminating manual coordination and protecting revenue across Travel, Mobility and Logistics.
Platform and Technology Partnerships
Every enterprise has the data. The challenge is acting on it across multiple systems and teams. Delays between identifying an issue and resolving it affect operations, revenue, and customer experience. Three KPIs reveal the true cost of that gap.
Operational context lives across booking systems, ERPs, CRMs, monitoring tools and dashboards. No single view. No single truth. No single moment of clarity.
Operations, data teams and systems often need to work together before an issue can be resolved. Every handoff is a delay. Every delay is a cost.
Operational delays affect service levels, customer experience and financial performance. The longer the gap, the higher the cost, and the harder it becomes to recover.
We architect and deploy across the full operational intelligence stack, data engineering, agentic AI, intelligent automation, product engineering, platform operations and integration services, from data capture through to agentic decision-making and process automation. Each practice is embedded, accountable and outcome-driven.
The data foundation for operational intelligence, connecting enterprise systems so operations teams have the context they need to make timely decisions.
AI agents that monitor operations, evaluate options and execute decisions in real time. They detect issues as they happen, reason across operational context and take action automatically, escalating when human judgement is required.
Turning operational decisions into execution. We design automation systems that connect AI decisions to the workflows that run your business, eliminating manual steps, reducing delays and keeping operations moving without constant human intervention.
Building and modernizing the platforms that power enterprise operations, using AI to accelerate engineering, improve reliability and reduce delivery risk. Delivered across Microsoft Azure, AWS and modern cloud platforms.
AI-assisted operations that keep enterprise platforms reliable, secure and continuously running. We combine platform engineering with AI-driven monitoring, diagnostics and optimisation, ensuring the systems behind your operations stay resilient as data, decisions and automation scale.
Real-time operational control environments for airlines, fleets and mobility networks, detecting disruptions, evaluating response options and coordinating actions across booking, dispatch and service systems.
Live digital replicas of ports, logistics hubs and complex infrastructure, enabling simulation, anomaly detection and predictive optimisation of large-scale operations.
Closed-loop decision engines for travel agencies, tour operators and business travel platforms, detecting operational signals, evaluating options and executing automated responses.
AI-driven task and case management systems that route, prioritise and automate operational workflows across teams, systems and service processes.
AI-powered extraction, classification and validation of operational documents, automating invoices, bookings, confirmations and operational paperwork.
Continuous intelligence across fleets, infrastructure and operational assets, combining IoT signals, telemetry and operational data to detect issues and predict disruptions before they impact operations.
Proven frameworks to build AI-driven operations faster.
Your agentic AI for an exceptional customer experience. Automates offline corporate travel requests from Email, Slack, Teams and WhatsApp, cutting agent clicks from 172 to 1 and reducing request-to-book TAT from 23 minutes to 3.4 minutes.
JourneySight helps DMCs and tour operators coordinate itineraries, suppliers, guides, vehicles and guest logistics across complex travel programmes.
The operational engine that runs everything after the booking is confirmed, orchestrating every task, handoff and exception across travel ops, hospitality and airlines without manual intervention.
AssetSight provides continuous intelligence across fleets, vehicles and operational infrastructure using telemetry, anomaly detection and predictive signals.
CommandSight creates a digital twin of enterprise operations, giving teams real-time visibility across systems, assets and operational workflows.
Partnering with Infarsight has been a game changer. Their automation capabilities have not only streamlined our processes but fueled innovation, allowing us to bring new solutions to market faster than ever.
Anderson Hernandez
SVP Contact Centers & Operations
Infarsight engineers embed directly into your workflows, delivering systems at the intersection of engineering and operational delivery. Depth without the hiring cost.
A fully managed CoE combining industry expertise, engineering capacity and governance to run long-term transformation programs with measurable outcomes.
Fixed-scope engagements with defined operational outcomes, timelines and accountability. When you need results, not a team on retainer.
Start with an Operational Intelligence Assessment. We map your systems, identify decision bottlenecks, and design the AI architecture that automates operational execution.
Six pre-built AI operations solution categories, each addressing a distinct enterprise operational challenge. Every solution is engineered across Infarsight's five practices: Data Engineering, Agentic AI, Intelligent Automation, Product Engineering and Platform Operations.
What is a Digital Twin?
A digital twin is a continuously updated virtual replica of an operational environment, capturing every asset, constraint, workflow and relationship in real time. In enterprise operations, digital twins are used to simulate disruption scenarios, predict downstream impacts before they occur and coordinate decision-making across complex interdependent systems including ports, logistics networks, fleet operations and airline hubs.
Real-time operational command centers that unify every system signal, surface exceptions automatically and route actions across airlines, fleet and dispatch operations.
Live replicas of ports, logistics hubs and operational infrastructure, continuously updated from real data to support scenario simulation and coordinated decision-making.
Closed-loop AI decision engines for TMCs, DMCs, tour operators and travel agencies, from signal detection through to automated action without manual intervention.
AI-driven workflow routing and case management that eliminates manual coordination across operations teams, requests resolved automatically, not manually queued.
AI extraction, classification and routing of operational documents, invoices, bookings, shipping documents and contracts processed automatically without manual handling.
Continuous monitoring across fleets, energy assets and operational infrastructure using telemetry, predictive signals and anomaly detection, before failures impact operations.
We start with an Operational Intelligence Assessment to identify the right solution for your context.
A real-time operational command centre that unifies vessel movements, container flows, fleet positions, carrier schedules and gate throughput into a single intelligence layer, giving logistics operations a live operational picture and AI-driven response capability when disruptions occur.
A logistics control tower is a real-time AI command environment that unifies all operational signals, vessel AIS feeds, container positions, fleet telemetry, carrier schedules, gate throughput and supplier ETAs, into a single live operational layer. It detects disruptions before they cascade, evaluates response options against available capacity and constraints, and executes or routes corrective actions automatically. It is not a dashboard, it is an active decision engine that monitors, evaluates and acts.
Vessel AIS data contains the early signal. By the time a late ETA reaches the operations team through manual channels, the berth reallocation window has passed, and the cascade into yard congestion, gate queues and demurrage has already started.
TOS, WMS, TMS, carrier portals and customs systems each hold part of the picture. No coordinator has a single view. Status updates arrive via email, phone and manual checks, introducing hours of lag into decisions that need to happen in minutes.
Delivery performance, demurrage accumulation and carrier SLA breaches are reviewed in weekly reports, not monitored in real time as operations unfold. By the time the report runs, the cost is already committed.
Responding to a supply chain disruption means coordinating changes across TMS, carrier portals, warehouse management, customs and customer notification systems simultaneously, a manual multi-step process that takes hours instead of minutes.
Vessel AIS feeds, container IoT sensors, fleet telematics, TOS and WMS data, carrier APIs and customs systems are ingested via Kafka streaming pipelines and normalised into a single operational data layer using Databricks. The Condense/Zeliot platform handles IoT device connectivity at scale.
AI agents monitor vessel ETAs, container dwell times, fleet positions and carrier SLA exposure continuously, detecting anomalies before they escalate. When a disruption is detected, agents evaluate response options against berth capacity, yard layout, carrier alternatives and SLA priorities, and route the optimal response for execution or human confirmation.
SCADA, OPC-UA, Modbus and terminal equipment protocols for port operations. REST and EDI for carrier and customs systems. MQTT for IoT device and fleet connectivity via AWS IoT Core or Azure IoT Hub. Infarsight's integration practice maintains all connections post-deployment.
A control tower for a live port or logistics network cannot have planned downtime. Platform operations ensures 99.9% uptime SLA, real-time alerting on integration failures, security compliance and continuous monitoring of the data and AI layer.
The analytics and ML layer, processing logistics telemetry, training predictive ETA models and running the anomaly detection layer that feeds the control tower AI agents.
Real-time IoT data streaming from terminal equipment, vehicle telematics and port sensors, the data foundation the control tower runs on.
Cloud-native IoT connectivity and device management for terminal equipment, fleet vehicles and infrastructure sensors at enterprise scale.
Pre-built control tower UI, signal aggregation and asset telemetry layers, reducing time to a live logistics intelligence programme.
Pre-built operational intelligence UI combining a live signal feed, AI decision inbox and exception management layer. Deployed as the operator-facing command environment for logistics networks and port operations.
Explore CommandSight →Continuous monitoring of terminal equipment, fleet vehicles and logistics infrastructure, providing the asset intelligence layer that feeds the control tower with real-time health, location and performance signals.
Explore AssetSight →We start with an operations audit, mapping your current data sources, integration gaps and the highest-cost disruption scenarios in your logistics network.
A continuously updated virtual replica of your port or terminal, every berth, every container position, every vessel ETA, every piece of equipment, enabling operations teams to simulate decisions, predict cascade disruptions and coordinate the physical operation through a single live model.
A port digital twin is a continuously updated virtual model of the physical terminal, ingesting vessel AIS data, container sensor feeds, equipment telemetry, gate camera data and TOS records to maintain a live, accurate representation of operations. Unlike a static dashboard that shows historical data, a digital twin reflects the terminal as it exists right now, and simulates how it will look in 2, 4 and 8 hours based on current trajectories. Operations teams use it to make berth allocation, yard staging and equipment deployment decisions before committing to them in the physical world.
Berth planners work from spreadsheets and VHF radio updates. Vessel ETAs change hourly based on weather, port priority and cargo loading delays. Without a live model that updates as ETAs shift, berth plans are stale before the ink dries.
Dwell time accumulates in specific yard blocks while others sit empty. Without a live yard model, restaging decisions are made on experience rather than data, creating congestion, double-handling costs and missed departure windows.
Crane breakdowns, straddle carrier failures and gate system outages are discovered when they occur, not before. Terminal equipment has telemetry signals that predict failures 24 to 72 hours in advance when monitored continuously.
Demurrage builds when berth planning, yard staging and gate release are not coordinated in real time. A vessel arrives on schedule but the yard has not been cleared. The cost is avoidable, but only if the coordination happens before the ship arrives.
Vessel AIS feeds, container RFID and sensor data, terminal equipment telemetry (cranes, straddle carriers, RTGs), gate CCTV and OCR, TOS records and weather feeds, all ingested and synchronised in real time via Kafka streaming pipelines using Zeliot's Condense platform for device connectivity.
The digital twin model itself, built using Azure Digital Twins or AWS IoT TwinMaker, maintains a live graph of berths, containers, vessels, equipment and relationships. The simulation layer evaluates proposed berth reallocations and yard restaging decisions against current terminal state before operations teams commit.
AI agents monitor the digital twin continuously, detecting developing yard congestion, approaching demurrage thresholds, equipment health anomalies and gate throughput bottlenecks before they become operational incidents.
Terminal Operating System (Navis N4, SPARCS), Vessel Traffic Service (VTS), SCADA protocols (Modbus, OPC-UA) and crane/RTG control systems, all connected through Infarsight's integration practice using the appropriate industrial protocol layer.
Microsoft's enterprise digital twin platform, graph-based live models of port terminal assets, relationships and operational state with real-time update and simulation capability.
IoT device connectivity and real-time data streaming from terminal equipment, vessel tracking systems and port sensors, the live data layer that keeps the twin current.
Real-time event streaming via Kafka and predictive analytics via Databricks, processing the high-throughput telemetry that port operations generate and running the ML models that detect anomalies in terminal state.
Pre-built asset telemetry connectivity and control tower interface layers, reducing time to a production digital twin programme.
Pre-built connectors for terminal equipment protocols, cranes, RTGs, straddle carriers and gate systems. Provides the continuous telemetry layer that feeds the digital twin with real-time equipment state and predictive health signals.
Explore AssetSight →The command-layer interface that sits above the digital twin model, presenting the live terminal state, surfacing AI recommendations and routing decisions to the right operations team member.
Explore CommandSight →We start with a data and systems assessment, mapping the terminal data sources, integration requirements and the specific operational decisions the digital twin will support.
Closed-loop AI decision systems for the moments that cost travel businesses the most, flight disruptions, booking exceptions, supplier failures and guest escalations. Built for TMCs, airlines, DMCs, OTAs and hotels where the gap between event and action is measured in lost revenue.
Decision intelligence for travel operations is the AI layer between your operational data and the actions your teams need to take, handling the routine, consistent decisions automatically and delivering fully-contextualised decisions for the complex ones. A flight change, a supplier non-confirmation, a guest escalation, a booking exception: each event triggers a decision process that today involves multiple systems, multiple people and avoidable delay. Decision intelligence closes that loop, in seconds, at scale, with an audit trail.
When a flight is cancelled or delayed, rebooking decisions happen after the disruption is confirmed, not while the operational window to act is still open. Passengers are already affected before the team has a full picture of options.
Booking exceptions and supplier failures require context from GDS, PMS, CRM and supplier systems simultaneously. Teams have one system open and three more unchecked. The right decision requires complete context, which rarely arrives in time.
A yield exception handled at 9am is handled differently at 9pm. Quality depends on individual experience, not encoded business rules that apply consistently across the whole operation.
Hotel rate decisions, tour operator pricing adjustments and airline ancillary yield decisions that wait for a human review cycle miss the pricing window. Automated decision intelligence executes yield logic in real time against live demand signals.
Decision intelligence is not a single product, it is built from the intersection of data engineering, agentic AI, intelligent automation, integration and platform operations.
GDS feeds (Amadeus, Sabre), PMS systems (Opera, Mews), CRM, supplier APIs and live flight data connected into a unified data layer. Every decision agent draws from the same real-time context.
AI agents monitor operational signals continuously, detecting IRROPS, booking exceptions, supplier failures, yield anomalies and duty of care triggers. Each agent evaluates, selects a resolution and either executes or escalates with full context.
Once a decision is made, execution happens through Power Automate for Microsoft-stack workflows and Appian for complex case management requiring approval chains and audit trails. Rebooking confirmations, supplier notifications and guest communications are fully automated.
Live connections to Amadeus, Sabre, Travelport, Navitaire, Opera, Mews and direct supplier APIs, ensuring decision agents always have the full picture.
Microsoft workflow automation for executing decisions across Microsoft 365, Dynamics and connected travel systems.
Low-code case management for complex travel decision workflows requiring multi-party approval, compliance tracking and full audit trails.
GPT-4o and Phi models for IRROPS triage, yield decision support and NLP for unstructured supplier communications.
Pre-built travel decision logic, GDS connectors and workflow templates.
Pre-built decision agents for IRROPS triage, policy compliance checking and booking exception resolution. Request-to-decision: 23 minutes to 3.4 minutes.
Explore TripSight →Supplier notifications, team assignments, status tracking and escalation management across the full post-booking operations layer.
Explore TaskSight →We start with a decision audit, mapping the highest-cost decision delays across your travel operations and designing the intelligence layer to close them.
AI-driven workflow routing and case management deployed across Travel, Mobility, Logistics and Enterprise Operations, every incoming task detected, classified, routed and resolved automatically, with escalation only where genuine human judgement is required. Built on Power Automate, Appian and the platforms your operations already run on.
Task orchestration is the automated routing, prioritisation and execution of operational workflows across systems, teams and service processes. Instead of coordinators manually triaging and assigning work, AI agents detect incoming tasks from any channel, email, booking system events, IoT alerts, customer portals, internal tickets, classify them by urgency and operational context, route them to the appropriate team or automated workflow, and track resolution against SLA targets. It is the layer that removes coordination overhead from operations, freeing teams to handle the decisions that genuinely need human involvement.
Task orchestration is not industry-specific, it applies wherever high-volume workflows are currently coordinated manually. Here is what it looks like in practice across the industries Infarsight serves.
Supplier non-confirmations, schedule change notifications, IRROPS rebooking queues, modification requests and refund processing, all routed automatically by priority, policy and SLA. TMC agents handle the exceptions that require negotiation, not the ones that have a deterministic resolution.
Vehicle fault alerts from telematics are classified by severity, matched to available technicians and maintenance slots, and routed for scheduling, with SLA-based prioritisation for vehicles on active routes. Unplanned breakdowns generate emergency work orders and fleet reassignment tasks simultaneously.
Document verification tasks, customs declaration queues, cargo release approvals and inspection scheduling, orchestrated automatically across terminal operators, customs agents and freight forwarders. Exceptions flagged for human review arrive with complete document context and compliance status.
Room readiness tasks, guest service requests, maintenance work orders and check-in coordination across multi-property hotel operations, all assigned, tracked and escalated automatically. Operations managers see completion status in real time rather than discovering delays at incident.
Email inboxes, booking system events, IoT device alerts, CRM queues, customer portals and internal ticketing systems, all connected into a unified task intake layer where every signal is captured, contextualised and enriched before routing begins.
AI agents classify each incoming task by type, urgency and operational context, applying configurable business rules to determine the routing path, SLA target and response type. Novel task types that fall outside existing rules are flagged for human classification and used to train routing logic over time.
Task execution is delivered on the workflow platform the client already operates: Power Automate for Microsoft-stack organisations, Appian for complex multi-party case management and compliance workflows, ServiceNow for IT and enterprise service management environments. Infarsight does not require platform replacement, it builds the orchestration intelligence layer on top of what you already run.
GDS, PMS, CRM, ERP, TMS, WMS, booking engines, supplier APIs and IoT platforms, all connected as task sources. Every system that generates work also gets the status feedback that keeps downstream operations informed.
Infarsight builds task orchestration on the platform that fits your existing estate, not a new tool that requires adoption.
Microsoft-native workflow automation — ideal for organisations already on Microsoft 365 and Dynamics. Infarsight builds complex multi-step orchestration flows on Power Automate with AI-driven routing and classification layers on top.
Low-code case management platform for complex operational workflows requiring structured approval chains, regulatory compliance tracking, multi-party coordination and full audit trail. Deployed for customs workflows, compliance processes and multi-stakeholder travel exceptions.
Enterprise service management and ITSM workflow orchestration for organisations using ServiceNow as their operational backbone. Infarsight extends ServiceNow with AI classification and cross-system routing layers that connect it to operational data sources beyond the IT domain.
The travel-specific orchestration accelerator, pre-built workflows, supplier connectors and task routing logic for TMCs, OTAs and hotel groups.
Pre-built orchestration for the full post-booking workflow layer: supplier confirmation chasing, schedule change detection, IRROPS exception routing, refund processing, duty of care monitoring and customer communication management. Reduces post-booking manual handling by 80% and saves 6 hours per operations team member per day.
Explore TaskSight →No. Infarsight builds the AI orchestration intelligence layer on top of the workflow platform you already operate. Power Automate, Appian and ServiceNow remain the execution engines, Infarsight adds the AI classification, routing logic and cross-system task detection layer that those platforms lack natively. Platform replacement is never required.
A ticketing system records and tracks tasks, humans still triage, assign and chase resolution. AI task orchestration detects tasks from any inbound channel automatically, classifies them without human triage, routes them to the right team or automated workflow and monitors resolution against SLA targets, escalating only when thresholds are breached. The coordination overhead that ticketing systems still require is eliminated.
A focused programme covering one operational domain, post-booking exception management for a TMC or maintenance work order routing for a fleet operator, typically deploys in 4 to 6 weeks using TaskSight's pre-built connectors and routing logic. Broader multi-domain programmes typically run 8 to 12 weeks from data assessment to production. The primary variable is integration complexity, not orchestration logic build time.
We start with an operational workflow assessment, mapping the highest-volume manual coordination tasks and the platforms your operations already run on.
AI extraction, classification and routing of operational documents, invoices, booking confirmations, shipping documents, contracts and compliance records processed automatically, without manual handling, at enterprise scale.
What is Document Intelligence?
Document intelligence is the AI-powered extraction, classification and validation of data from operational documents, invoices, booking confirmations, shipping documents, supplier vouchers and compliance records. It combines OCR, NLP and validation logic to automate document processing workflows that currently require manual review, reducing processing time from hours to seconds and eliminating the silent errors that manual data entry creates.
In travel, logistics and enterprise operations, documents, invoices, booking forms, shipping manifests, supplier contracts, arrive in inconsistent formats, require manual data extraction, and sit in queues waiting for a human to read and process them. Every document that waits is a decision delayed.
Documents arrive from every channel, email attachments, supplier portals, scanned fax, EDI feeds, customer uploads and API pushes. Data Engineering connects every source into a unified ingestion layer, ensuring every document is captured, timestamped and queued for processing regardless of format.
AI extracts structured data from unstructured documents, regardless of format, layout or template. It classifies the document type, validates extracted fields against business rules, identifies discrepancies and routes exceptions to the right human with a confidence score and recommended resolution.
Once data is extracted and validated, Intelligent Automation executes the downstream actions, posting to ERP, triggering payment workflows, updating booking systems, filing in compliance repositories and notifying relevant stakeholders. No manual data entry. No re-keying across systems.
A purpose-built document operations interface showing every document in flight, its status, extracted data, validation result and action taken. Exception queue for documents requiring human review, with AI-recommended resolution and one-click approval.
We start with a document audit, mapping your highest-volume document types, extraction requirements and downstream system connections.
Continuous intelligence across fleets, vehicles, energy assets and operational infrastructure, using telemetry, IoT data, anomaly detection and predictive signals to detect failures, inefficiencies and risks before they impact operations.
What is Real-Time Asset Intelligence?
Real-time asset intelligence uses continuous telemetry, IoT sensor data and AI anomaly detection to monitor the health, location and performance of operational assets, vehicles, equipment, chargers, industrial machinery, and predict failures before they occur. It moves fleet and infrastructure management from reactive maintenance to predictive operations, reducing unplanned downtime and extending asset life.
Organisations managing large fleets, energy infrastructure or industrial assets typically discover problems after they happen, through a breakdown, a missed SLA or a maintenance backlog. The cost of reactive operations is a multiple of the cost of predictive operations.
Real-Time Asset Intelligence begins with connecting every asset to a live data layer. Infarsight Data Engineering builds the IoT ingestion pipeline that captures vehicle telemetry, equipment sensor data, energy meters and environmental feeds, processed at scale with sub-second latency.
AI models continuously analyse telemetry streams for anomalies, degradation patterns and failure precursors. When a pattern indicates an emerging failure, vibration drift, temperature spike, oil pressure drop, the agent predicts the remaining useful life, calculates operational impact and triggers the appropriate response before the asset fails.
When AI identifies a maintenance need, Intelligent Automation executes the response, creating work orders, scheduling technicians, notifying dispatch, updating asset availability and propagating the change across all dependent operational systems. No manual ticketing. No missed handoffs.
A purpose-built asset health platform showing live status, predictive health scores, maintenance schedules and operational KPIs across every asset in the fleet or infrastructure estate, in a single, real-time view accessible by operations, maintenance and management teams.
For Asset Intelligence to be trusted, the telemetry pipeline must be reliable. Platform Ops governs every data feed, detecting gaps, latency anomalies and sensor outages before they corrupt the predictive model or trigger false alerts. Data governance ensures asset data is accurate, complete and audit-ready.
Vehicle health monitoring, predictive maintenance, EV battery degradation tracking and charging network optimisation, reducing downtime, fuel costs and unplanned service events across large fleet operations.
Power generation, pipeline, turbine and industrial equipment monitoring, failure prediction, load optimisation and maintenance scheduling across geographically distributed infrastructure.
Crane health monitoring, container handling equipment condition tracking and port yard asset intelligence, maximising throughput by keeping critical equipment operational and maintenance aligned with vessel schedules.
Asset intelligence ingests telemetry from vehicle CAN bus and OBD-II interfaces, IoT sensors (temperature, vibration, pressure, current), GPS and GNSS location feeds and scheduled maintenance records. ML models trained on historical fault patterns detect anomalies in these real-time streams, flagging at-risk assets typically 24 to 72 hours before a fault would cause a service disruption.
Asset intelligence programmes have been delivered for fleet operators (commercial vehicles, logistics), EV charging network operators, port terminal equipment operators (cranes, straddle carriers, gate systems), energy and industrial infrastructure and airline ground equipment. The underlying approach, continuous telemetry, anomaly detection, predictive alerting, applies wherever assets have sensor data and downtime has a material cost.
Both. Infarsight can deploy the full IoT data stack using Condense (the Zeliot real-time data platform) for data ingestion and streaming, or connect to existing IoT platforms including AWS IoT Core, Azure IoT Hub and Siemens MindSphere. The integration services practice handles device connectivity across MQTT, OPC-UA, Modbus and proprietary telematics protocols.
We start with an asset audit, mapping your current monitoring coverage, telemetry sources and highest-cost unplanned maintenance events.
A real-time operational command center that unifies every system signal, surfaces every exception and routes every decision, giving operations teams a single source of truth, powered by AI, across airlines, fleets and dispatch.
TripSight connects airline, hotel and ground systems into a single AI-driven view, with disruption handling, automated rebooking, yield optimisation and passenger journey intelligence all in one platform.
FleetSight gives fleet operators live vehicle health, predictive maintenance alerts, route optimisation and EV network state management, all in a single control tower powered by Zeliot IoT telemetry.
Traditional dashboards report what happened, hours ago, formatted for review, requiring a human to interpret and decide what to do. They create awareness, not action.
An operational control tower doesn't just show data, it detects anomalies, routes decisions and executes actions. It transforms operational awareness into operational outcomes, automatically.
In airline ops, the average time from delay detection to rebooking action is 34 minutes. With TripSight's control tower, the same action is executed in 2.4 seconds, before passengers reach the gate.
We deploy TripSight or FleetSight in weeks, with pre-built connectors for your existing systems.
Closed-loop agentic decision engines and digital twin systems that eliminate decision latency at its root. DecisionSight models your operational state, simulates scenarios and executes, or escalates when human judgment is required.
In complex operations, airlines, ports, fleets, logistics, the decision window is always shorter than the decision process. Until now.
At 07:14, an aircraft lands 38 minutes late. Three teams work in parallel. By 07:26, 34 connecting passengers have already passed their rebooking window. The aircraft swap option was available for 11 minutes. Nobody saw it in time.
Dashboards show what happened. Reports arrive hours late. Meetings are called to discuss what to do. By the time action is taken, the window has closed, and the cost has already been incurred.
It is eliminating the gap between operational event and corrective action by design, replacing the human decision-processing bottleneck with an agentic system that reasons and acts at machine speed.
DecisionSight maintains a live digital twin of your operational state, continuously updated from every system. When an event occurs, it simulates outcomes, selects the optimal action and executes, in seconds.
Our proprietary Decision Intelligence platform, digital twin, scenario simulation and automated decision execution for Travel and Mobility operations.
Explore DecisionSight →We begin with a decision latency audit, mapping your most costly operational decision delays and sizing the automation opportunity.
The intelligence foundation that powers every AI decision, built on Condense and Zeliot. Data that is current, clean, connected and contextual. Not just dashboards. Not just reports. Data that acts.
Zeliot's real-time data platform (Infarsight investment), pre-built connectors for GDS, PMS, CRM, IoT and ERP systems with semantic data models and built-in governance. The data backbone powering TripSight, FleetSight and DecisionSight.
Infarsight's strategic IoT investment, real-time vehicle telemetry, asset location tracking, geofencing and edge processing. The sensor and telemetry backbone powering FleetSight and the Mobility COE. 284+ vehicles tracked live.
Start with a data audit, we map your sources, gaps and highest-value pipeline opportunities.
Condense is the real-time data streaming platform from Zeliot — in which Infarsight holds a minority investment. Purpose-built to turn raw operational data from Travel, Mobility and Logistics systems into decision-ready data pipelines at enterprise scale.
What is Condense?
Condense is a real-time operational data streaming platform developed by Zeliot, in which Infarsight holds a minority investment. It provides pre-built connectors to Travel, Mobility and Logistics systems, semantic data models and real-time pipeline infrastructure, forming the data foundation that Infarsight deploys for agentic AI and intelligent automation programmes requiring low-latency, high-quality data.
Condense integrates natively with Zeliot.in, Infarsight's strategic IoT investment, for real-time vehicle and asset telemetry in Mobility deployments.
Visit zeliot.in →Request a platform demo, we'll walk through a live deployment in your operational context.
Your agentic AI for an exceptional customer experience. TripSight automates offline corporate travel requests from Email, Slack, Teams and WhatsApp, reducing multi-hour request-to-book TAT to minutes. Travel agents go from 172 clicks per request to one.
What is TripSight?
TripSight is Infarsight's agentic AI delivery accelerator for corporate travel booking operations. It processes offline travel requests via email, Slack, Teams and WhatsApp, automating policy checking, GDS querying and booking confirmation. Request-to-book time: 23 minutes to 3.4 minutes. Agent clicks per booking: 172 to 1. Deployed for TMCs, corporate travel teams and OTAs with GDS integration across Amadeus and Sabre.
Every travel request that arrives by email, WhatsApp or Slack kicks off a manual chain, login to email, assign to agent queue, identify customer type, open GDS, fire commands, copy-paste itinerary, search templates, write quote, await confirmation. That is the status quo TripSight replaces.
Multiple quote revisions lead to back-and-forth emails. Every revision requires the agent to re-open GDS, re-fire commands and re-assemble the response manually.
Teams stretched thin handling high volume requests build backlogs that jeopardise SLA. During peak season, the gap between demand and capacity becomes a revenue risk.
Agents perform alt-tab constantly, collecting data from GDS, CRM, email and hotel systems in separate windows. Every system switch adds time, adds error risk and fragments the customer view.
In a bidding situation, the first quote wins. When agents take 15–20 minutes per quote, clients turn to competitors. The cost of slow TAT is not just operational, it is direct revenue leakage.
Advanced AI reads and interprets travel requests in emails like a human, accurately identifying destinations, dates, passenger count, class of service, preferences and any special requirements. Handles acronyms (DXB to MCT), spelling errors (rnd trip → round trip) and ambiguous phrasing without agent intervention.
The rule engine ensures compliance with corporate travel policies, applies GDS-negotiated deals and leverages customer profiles for personalised, cost-effective bookings. Policies configured once, applied automatically across every request, every time.
Auto-pilot activates for high-volume requests, quotes, bookings, date changes, cancellations and refunds, sending responses directly to customers without agent involvement. Co-pilot mode assigns to agents for review before sharing, ensuring speed with control. Managers choose which workflows go fully automatic.
100 scenarios pre-trained out of 456 total, covering one-way, round-trip and multi-city flights; single and multi-pax; preferred airline, class of service, seat preference, meal preference, baggage, special needs and policy adherence. Hotels, car, visa and all-services combinations ready out of the box.
Command center to view response times and SLAs, customer satisfaction scores, agent performance, channel volumes and ticket throughput in real time. Managers see the full picture without asking agents for status updates.
TripSight works inside the tools agents already use. Requests from any channel are captured, classified and processed through the same automation layer. No new system to learn. No change management required for agents, the intelligence is invisible.
All data encrypted in transit and at rest. SHA-256 encoding and data encryption at rest across all customer data stores.
Secure login using SSO, IP whitelisting for network-level access control and JWT authentication for API integrations.
Data vault for customer data, sensitive data masking and GDPR-compliant processing. Built for regulated enterprise travel environments.
Connects to Amadeus, Sabre, Travelport, Zendesk, Freshdesk, Salesforce, ServiceNow, Zoho, Jira, Slack, Teams, Gmail, Outlook and more, without replacing existing tools.
We start with a request-to-book workflow audit, mapping your current email volumes, average TAT and highest-cost manual steps, then show you exactly what automation covers from day one.
JourneySight helps DMCs and tour operators coordinate itineraries, suppliers, guides, vehicles and guest logistics across complex travel programmes, reducing coordination delays, improving visibility across programmes and enabling faster response to disruptions during tours.
What is JourneySight?
JourneySight is Infarsight's post-booking delivery accelerator for DMCs and tour operators. It automates the coordination of itineraries, suppliers, guides, vehicles and guest logistics across concurrent travel programmes, syncing live flight data, triggering supplier communications and managing exceptions before guests are affected. It replaces the manual programme coordination that consumes DMC operations capacity.
For DMCs and tour operators, the real work starts after the booking is confirmed. Coordinating suppliers, allocating guides and vehicles, managing guest communications across dozens of concurrent programmes, this is where operational capacity is consumed and margin is lost.
Ground suppliers, hotels, guides and transport providers managed through email and phone, with no single view of confirmation status across the programme.
When a flight is delayed or changed, the downstream impact on transfers, guides and programme timing is discovered manually, often after the guest has already arrived.
Coordinators spending hours per day on status chasing, amendment processing and manual reconciliation, overhead that scales with programme volume, not with value.
Operations teams managing multiple active tours simultaneously with no unified view, each programme tracked in a separate spreadsheet or system.
Every component of the programme, flights, hotels, excursions, guides, vehicles and restaurant bookings, tracked in a single operational view with confirmation status, timing dependencies and exception flags visible in real time.
JourneySight connects to live flight data feeds, vehicle dispatch adjusts automatically when flights are early, delayed or diverted. Guides and drivers notified automatically. Zero missed pickups from flight changes the operations team didn't see in time.
Automatic allocation of guides, vehicles and equipment across concurrent programmes, based on availability, skill set, location and programme requirements. Conflicts flagged before they become operational problems.
Supplier confirmations tracked across the programme, JourneySight sends, chases and logs all supplier communications automatically. Amendment instructions dispatched and acknowledged without coordinator involvement for routine changes.
Programme-level anomaly detection, hotel stop-sells, supplier failures, weather disruptions and schedule changes monitored continuously. JourneySight surfaces exceptions with impact assessment and resolution options before guests feel the disruption.
Pre-arrival itinerary sharing, in-destination updates, transfer reminders and disruption notifications sent automatically via guest's preferred channel, reducing inbound queries and ensuring guests always have current information.
DMCs and tour operators running complex multi-day programmes with multiple suppliers, guides and ground services see the highest impact. The operational benefit scales with programme complexity: the more suppliers to coordinate, the more flight changes to monitor and the more concurrent programmes running simultaneously, the greater the reduction in manual effort JourneySight delivers.
JourneySight monitors live flight data feeds continuously and cross-references them against booked itineraries. When a flight change, delay or cancellation affects a guest, the system automatically calculates the downstream impact on transfers, guides and accommodation check-in windows, triggering supplier communications and generating rebooking options before the DMC operations team would otherwise become aware of the disruption.
JourneySight operates alongside existing tour management platforms such as Tourplan, TravelBox and Travelogic, it does not require replacement. It adds the real-time intelligence and automation layer above them: live flight monitoring, automated supplier coordination and exception detection. Infarsight's integration services handle the connectivity to existing mid-office and supplier systems.
We start with a programme operations audit, mapping your current coordinator workflows and highest-cost manual coordination steps.
TaskSight is the post-booking operations automation engine that runs everything after the booking is confirmed.
What is TaskSight?
TaskSight is Infarsight's post-booking operations automation delivery accelerator. It orchestrates every workflow, task assignment and exception that follows a confirmed booking, across travel operations, hospitality and transportation. It connects back-office systems, supplier communications and customer touchpoints into a single accountable control layer, eliminating manual coordination.
TripSight manages the booking process, search, quote, confirmation. TaskSight manages everything after confirmation: service delivery, supplier coordination, exception handling and SLA management. Two platforms, one seamless traveller experience.
The booking platform does its job. The operational gap lives in everything that follows. The booking is confirmed, and then the chaos begins.
Tasks bounce between email, WhatsApp, spreadsheets and calls. Nothing is tracked. Accountability disappears the moment a booking is confirmed. Every handoff is a potential failure point, invisible to everyone except the person who dropped the ball.
Service failures, supplier delays and missed SLAs go undetected until a customer complains. Reactive management is the default. By then, the operational window to recover has passed, and the cost is already a customer experience problem.
Operations managers have no real-time view of what is outstanding, overdue or at risk. Decisions are made on memory, not data. Status updates require phone calls. Shift handovers require tribal knowledge. Performance is reviewed in reports, not acted on in the moment.
TripSight or external booking system confirms the reservation and fires an event to TaskSight.
TaskSight instantiates the relevant workflow template, hotel check-in, tour, transfer or flight service.
Roles, suppliers and deadlines auto-assigned based on service type, SLA and team availability.
Missed SLAs, supplier failures or customer changes trigger smart escalation and automatic re-routing.
Completion status, SLA adherence and quality scores feed live ops dashboards and client reports.
Configurable workflow templates for every post-booking service type. Triggers, conditions, parallel tasks and approvals, no code required. Templates encode the operational intelligence for every service: hotel, tour, transfer, airline, group booking.
Intelligent task assignment by role, skill and current workload. Deadline tracking, priority queues and completion verification across teams and suppliers. Every task has an owner, a deadline and a status, visible to everyone who needs to see it.
Real-time monitoring of SLA breach risk across every active task. Automated escalation trees route exceptions to the right human at the right time, before the customer notices, not after they complain. Every escalation carries full operational context.
Supplier task portals for hotels, transfer providers, guides and airlines. Two-way status updates eliminate check-in calls and chasing emails. Suppliers confirm, update and flag exceptions directly in the system, no more WhatsApp chains between coordinators.
Automated, personalised pre-trip and in-trip communications triggered by operational events, not scheduled blasts. Reminders, updates, disruption notifications and service confirmations dispatched at the moment they are operationally relevant.
Live operational KPIs, task completion rates, SLA adherence, exception volumes, team productivity and supplier performance scores, updated in real time. Managers see the full picture without asking for status updates.
Elimination of manual task chasing, status calls, email follow-ups and spreadsheet updates across every booking in operations.
Automated task routing replaces WhatsApp chains and email threads. Every handoff is tracked, timed and completed within system.
Real-time exception detection and escalation means SLA breaches are caught before customers notice, not after they complain.
Intelligent routing sends exceptions to the right person with full context. Resolution time drops from hours to minutes.
Not a generic task management tool repurposed for travel. TaskSight was designed from the ground up for the operational reality of post-booking, supplier networks, SLA chains, regulatory requirements and multi-timezone execution.
TaskSight is not delivered once and handed over. Infarsight teams stay embedded, continuously expanding workflows, tuning automation and building new use cases as your operations evolve. 10+ years in travel operations means we know where the exceptions live before you describe them.
Built on Microsoft Power Platform, Azure-native, REST API-first and compatible with Appian and UiPath automation layers. Connects TripSight, GDS, PMS, CRM, ERP, supplier portals and payment gateways, without displacing any existing system.
We begin with a structured operational assessment, mapping your post-booking workflows, identifying the highest-value automation opportunities and designing the architecture that connects your systems, teams and suppliers.
AssetSight provides continuous intelligence across fleets, vehicles and operational infrastructure, using telemetry, anomaly detection and predictive signals so potential failures, inefficiencies and operational disruptions can be detected earlier and resolved before they impact operations.
What is AssetSight?
AssetSight is Infarsight's real-time asset intelligence delivery accelerator, providing continuous monitoring, predictive maintenance signals and dispatch optimisation across fleets, EV charging networks and operational infrastructure. It ingests telemetry from vehicle CAN bus, OBD-II and IoT sensors, applies ML anomaly detection and triggers maintenance or dispatch actions before faults impact operations.
AssetSight connects every vehicle, machine and infrastructure asset to a live intelligence layer, turning raw telemetry into operational signals that predict, detect and prevent failures before they happen.
Every vehicle and asset emitting a live signal, location, health, utilisation, performance, aggregated into a single real-time view. No dark fleet. No unmonitored equipment. Asset state always current, always accurate.
AI models analyse telemetry streams for degradation patterns, vibration drift, temperature anomalies, oil pressure deviations, battery health decline, predicting failures days or weeks ahead. Maintenance scheduled proactively, not reactively after breakdown.
Telemetry ingested from vehicle OBD/CAN bus, IoT sensors, charging infrastructure and third-party telematics platforms. Data normalised, enriched and made available to the operational intelligence layer in sub-second latency.
Dispatch decisions driven by live vehicle health, location and availability, not just a vehicle list. Vehicles assigned based on condition, remaining range, route suitability and SLA requirements. Asset utilisation optimised continuously across the fleet.
Charging network state management, real-time availability, session monitoring, demand forecasting, fault detection and battery health tracking across distributed EV infrastructure. Charging schedules optimised against operational demand and grid costs.
When a predictive alert is triggered, AssetSight executes the response, work orders created, technicians scheduled, parts reserved, dispatch updated and stakeholders notified. No manual ticketing. The system acts on the intelligence it generates.
We start with an asset audit, mapping your current monitoring coverage, telemetry sources and highest-cost unplanned maintenance events.
CommandSight creates a digital twin of enterprise operations, giving teams real-time visibility across systems, assets and operational workflows. Disruptions can be detected earlier, decisions evaluated faster and actions coordinated across multiple systems from a single control layer.
Related: Digital Twins
A digital twin is a continuously updated virtual replica of an operational environment. See Digital Twins solution →
What is CommandSight?
CommandSight is Infarsight's operational command intelligence delivery accelerator, a unified layer that combines a digital twin of enterprise operations with a real-time decision inbox, signal feed and agent orchestration console. It gives operations leaders a single interface to see what is happening, what AI has already resolved and what requires a human decision.
CommandSight aggregates signals from every operational system into a live digital twin, then applies AI to detect anomalies, simulate response options and execute or route decisions. Operations teams see everything. Act on anything. From one interface.
Live command view of the entire operational state, every system signal, every active decision, AI vs human action ratio, financial exposure and SLA adherence updated in real time. The situational awareness layer.
The action center for decisions that require human judgment, all escalations in one prioritised queue, with full context assembled by AI, recommended resolution and one-click execution. Nothing falls through the cracks.
Real-time anomaly alerts from all connected operational systems, detected before they become incidents. Cross-system correlation identifies root cause and impact scope automatically, so teams respond to meaning, not noise.
AI agents coordinate across all connected systems to execute decisions, automatically for routine actions, with escalation for complex exceptions. Multi-system actions triggered simultaneously from a single decision. Full audit trail for every agent action.
Operational KPI dashboards, automation ROI tracking, agent performance monitoring and continuous improvement recommendations, built into the command layer so performance improvement is ongoing, not periodic.
A standard operations dashboard shows data. CommandSight shows the operational state, and acts on it. It combines a live digital twin of operations with an AI decision inbox, where agents surface resolved issues and pending escalations. Operators see not just what is happening, but what has already been resolved automatically and what requires a decision from them, reducing the cognitive load on operations teams significantly.
CommandSight has been deployed for airline operations control, fleet dispatch centres, port terminal operations and logistics networks. Any operational environment where multiple systems feed into a central decision point, and where the cost of slow or inconsistent decisions is measurable, benefits from the CommandSight architecture.
CommandSight sits above the integration layer. Infarsight's data engineering and integration services practices build the connectivity to booking systems, ERP, IoT platforms, CRM and operational tools, CommandSight then receives normalised, real-time operational signals from this data foundation. It does not require replacement of existing systems; it unifies them into a single operational view with AI-driven decision routing.
We start with an operational intelligence audit, mapping your data sources, decision flows and highest-cost manual interventions.
DecisionSight is a real-time operational decision intelligence system, detecting signals across all operational systems, evaluating options against business constraints and executing the optimal decision automatically. Beyond dashboards. Beyond alerts. Beyond reporting.
Most operational tools surface information. DecisionSight goes further, it models the operational state as a digital twin, simulates the projected outcome of every available response option, and executes the optimal decision automatically within defined governance boundaries.
Real-time signals ingested from every connected operational system, events, anomalies, threshold breaches and emerging risks detected the moment they appear.
The operational digital twin updates continuously, every entity, relationship and constraint reflecting the current real-world state within seconds of any change.
Before any action, DecisionSight simulates 3–5 response scenarios, projecting the downstream impact of each option across time, cost, SLA and operational constraints.
For decisions within confidence thresholds, DecisionSight executes automatically across all connected systems. For high-stakes exceptions, it surfaces to the right human with full context and recommended action.
A continuously updated digital replica of the operational environment, every asset, booking, crew member, resource and constraint modelled in real time. When something changes in the physical world, the twin updates within seconds.
Before executing any action, DecisionSight simulates the downstream impact of each available option, across time, cost, SLA exposure and customer experience dimensions. Decisions made with projected outcome visibility, not instinct.
Business rules, SLA thresholds, cost constraints, regulatory obligations and operational priorities encoded into the decision model, not as brittle IF/THEN logic, but as contextual constraints that apply dynamically to each unique situation.
Decisions don't produce recommendations, they trigger action. DecisionSight executes across all connected operational systems simultaneously, closes the loop in the digital twin and logs every action with its reasoning chain for compliance and audit.
Confidence thresholds define what the system decides automatically and what it escalates. Escalations surface with full context, simulated outcomes and recommended action, keeping humans in control of what matters while agents handle everything else.
Every decision, automated or human, feeds back into the model. DecisionSight learns from outcomes, adjusting confidence thresholds, improving scenario accuracy and expanding automation coverage as operational patterns evolve.
We start with a decision latency audit, mapping your highest-cost operational decision delays and designing the automation architecture.
Six delivery accelerators purpose-built for Travel and Mobility operations, each combining Data Engineering, Agentic AI, Intelligent Automation, Product Engineering and Platform Ops into a deployable product.
Operational data platform with pre-built GDS, PMS, CRM, IoT and ERP connectors. Semantic data models, governance and real-time pipelines. The data backbone powering every solution accelerator.
Real-time vehicle telemetry, asset intelligence and IoT data platform, Infarsight's strategic investment that powers FleetSight and the Mobility COE. 284+ vehicles tracked live. Edge processing for low-latency field intelligence.
Automates offline corporate travel requests from Email, Slack, Teams and WhatsApp, cutting agent clicks from 172 to 1 and reducing request-to-book TAT from 23 minutes to 3.4 minutes.
Coordinates itineraries, suppliers, guides, vehicles and guest logistics across complex travel programmes, with live flight sync and automated supplier communications.
The operational engine that runs everything after the booking is confirmed, orchestrating every task, handoff and exception across travel, hospitality and airlines without manual intervention.
Continuous intelligence across fleets, vehicles and infrastructure using telemetry, anomaly detection and predictive signals, failures detected before they impact operations.
Creates a digital twin of enterprise operations, real-time visibility across systems, assets and workflows with AI decision routing and one-click execution.
Real-time decision intelligence system — detects signals, evaluates options against business constraints and executes the optimal decision automatically.
Strategic technology partner delivering data engineering, agentic AI and operational intelligence for Bosch's global mobility programs.
Request a demo, we'll walk through the accelerators relevant to your operational context.
Infarsight Data Engineering services build the intelligence foundation that connects operational data to real-time business decisions, across ERP, CRM, IoT and operational systems. We build data pipelines and platforms designed for operational action, not just reporting.
What is Enterprise Data Engineering?
Enterprise data engineering is the practice of designing, building and maintaining the data pipelines, platforms and governance systems that connect raw operational data to business decisions. It covers data ingestion, transformation, quality management, real-time streaming and the infrastructure that makes AI and analytics possible at scale.
Siloed across ERP, CRM, IoT and BI systems with no unified layer. Teams can't trust what they're looking at. Decisions are made on contested data.
Reports take hours or days. By the time data reaches decision-makers, the operational window has closed, and the cost of inaction has already compounded.
One-off scripts, manual extracts and fragile integrations break under scale, costing time, trust and money. Data quality collapses within 6 months of go-live.
Finance, Operations and Technology each have a different version of the same number. Every team defines "customer" differently. Decisions are built on a flawed foundation.
"We're trying to do AI. But we haven't even engineered our data like a product."
, Chief Digital Officer, Ports (USA)
We understand Travel, Ports and Mobility deeply. Our engineers don't just build pipelines, they understand the operational decisions those pipelines need to serve.
We connect data engineering directly to the automation and agentic AI layers. Your pipelines don't end at a dashboard, they feed the decision systems that run your operations.
Our strategic investment in Condense reduces time to production-grade pipelines by up to 60%, pre-built connectors, governed templates and observability tooling built in.
We embed engineers into your operations for long-term data quality ownership. Unlike project-based delivery, we stay accountable for the health of the data systems we build.
Most organisations have data. Very few have data that is current, clean, connected and contextual enough to drive operational decisions without human intervention.
Available at the moment the decision needs to be made, not hours or days later.
Governed, validated and consistent across every system that touches it.
Unified across ERP, CRM, IoT and operational systems into one coherent layer.
Enriched with the operational metadata needed to trigger the right action automatically.
Each track is designed for a specific data problem. We deploy what your operation actually needs.
Your pipelines need to run like clockwork, monitored, maintained and trusted every day.
Real-time pipelines that ingest, enrich and trigger actions the moment an event occurs.
Audit every byte from ingestion to insights, identify hidden risks and fix broken pipelines before they break operations.
Edge-to-boardroom ingestion, capturing data from cameras, meters, IoT devices and machines into scalable pipelines.
Migrate legacy infrastructure to cloud-native architectures without disrupting live operations.
Turning data into self-serve intelligence that empowers operational decisions, not just executive reports.
Creating a single, trusted version of your most critical operational data, customers, assets, locations, products.
Infarsight's strategic investment in Condense — a real-time streaming platform that reduces time to production-grade pipelines by up to 60%. Pre-built connectors for Travel, Hospitality and Mobility source systems. Governance, lineage and observability built in from day one.
From operational problem to production data system, in a repeatable, governed process.
Data audit, source mapping, pain sizing. 1–2 weeks.
Architecture blueprint, pipeline design, governance framework. 2–3 weeks.
Pipeline development, integration, data quality rules. 4–12 weeks.
Monitoring, incident management, performance tuning. Ongoing.
Query optimisation, new source onboarding, quality improvement. Continuous.
Also see: Real-Time Operational Data Platforms solution → | Condense data platform → | Agentic AI — what the data feeds →
We begin with a Data Readiness Assessment, mapping your current landscape, identifying highest-value opportunities and designing the architecture.
Infarsight Agentic AI engineering builds the decision layer that sits between your operational data and the actions your business needs to take, closing the gap between operational event and automated response, at enterprise scale.
What is Agentic AI?
Agentic AI refers to AI systems that autonomously perceive operational signals, reason across contextual data and execute decisions across connected enterprise systems, without requiring human intervention at each step. Unlike AI that produces recommendations, agentic systems close the loop: they act, escalate and learn from operational outcomes.
Every agent we build has a defined operational decision to make, a measurable outcome to drive and a governance framework that keeps humans in control. We don't build AI for its own sake.
We understand Travel, Ports and Mobility deeply. Our agents are trained on the operational logic of industries we've been embedded in for over a decade, not on generic enterprise patterns.
Our agents sit between Infarsight Data Engineering and Product Engineering. They receive decision-ready signals and execute into operational platforms, all built by us, all connected.
Human-in-the-loop controls, explainability, audit trails and drift monitoring are designed into every agent we build, not added after a governance review flags a risk.
It perceives a situation, reasons across available context, decides on an action and executes, or escalates when human judgment is needed.
From operational systems, events, anomalies, thresholds and alerts, the moment they occur.
Across context, rules, constraints and operational goals, not hard-coded IF/THEN logic.
From available options, or flags for human review when the decision requires judgment.
Booking, dispatch, notification, reroute, alert, the decision lands in production, not a report.
Designing the agents, orchestration layer and tool ecosystem that powers autonomous operational decision-making.
Encoding operational knowledge into agents that make the right call, consistently, at the speed the operation demands.
Keeping humans in control where it matters most. Agentic AI without human oversight is a risk, but human oversight without design is a bottleneck.
Keeping agents reliable, transparent and compliant, in production, over time. Governance is not an afterthought; it is designed into every agent we build from day one.
Connecting agents to the systems they need to perceive, decide and act, without replacing the infrastructure already in place.
We are not tied to any single AI provider. We select foundation models, frameworks and retrieval systems based on the decision context, latency requirements and governance needs of each use case.
Operational decisions that previously took 20–60 minutes are executed by agents in under 2 minutes, across disruption, dispatch and scheduling workflows.
Agents handle the volume of operational exceptions that previously required coordinator intervention, freeing teams for judgment-intensive work.
TripSight — Infarsight's proprietary travel operations accelerator, resolves 95% of passenger disruption cases without human involvement.
Continuous agent operation eliminates the wait time between operational event and corrective action, the gap where cost and customer impact accumulate.
From operational decision problem to production AI agent, in a governed, risk-managed process.
Decision mapping workshop, agent candidate scoping, data & signal audit, risk & governance brief. 1–2 weeks.
Agent architecture, decision boundary definition, HITL framework design, tool & API mapping. 2–3 weeks.
Agent development, integration delivery, sandbox testing, HITL workflow build. 4–10 weeks.
Decision monitoring, escalation management, quality scoring, governance reporting. Ongoing.
Decision scope expansion, agent retraining, new integrations, performance optimisation. Continuous.
Also see: Data Engineering — what feeds the agents → | DecisionSight accelerator → | Decision Intelligence Systems →
We start with a Decision Mapping Workshop, identifying the highest-value operational decisions in your business, mapping the signals available and designing the first agent use case.
Infarsight Intelligent Automation builds the execution layer, automating the structured, repeatable processes that consume operational capacity through RPA, workflow orchestration and AI-augmented processing, so your teams focus on what only humans can do.
What is Intelligent Automation?
Intelligent automation combines RPA, AI-augmented processing and system integration to automate the structured, high-volume operational processes that consume team capacity. It goes beyond rules-based scripting, handling unstructured inputs, managing exceptions intelligently and orchestrating workflows across enterprise systems without manual handoffs.
Every hour your teams spend on repetitive, structured tasks is an hour not spent on the work that moves the business.
Invoicing, reconciliation, report generation, data entry, status updates, essential but mechanical. They consume headcount that should be focused on operational performance.
Manual processes introduce errors at scale. A missed field, a wrong value, a delayed update, each one creates downstream rework, compliance risk and customer impact.
Data trapped in one system that needs to be in three others. Integration gaps are filled by people doing manual re-entry, creating latency, errors and invisible dependencies.
When process volume grows, the default response is to hire. Organisations that haven't automated structured processes are forced to grow teams linearly with operational demand.
Our automation programmes are built around the workflows of Travel, Ports and Mobility. We understand the exceptions, the edge cases and the integration complexity of these industries.
We design automation as a managed programme with a coherent architecture. Every bot, workflow and integration connects into a governed estate, not a patchwork of point tools that degrade independently.
When processes involve unstructured inputs, classification decisions or judgment-based exceptions, we layer in AI. Intelligent Automation handles more than basic bots.
Our automations receive signals from Data Engineering and execute decisions from Agentic AI, making Intelligent Automation the action layer of a fully connected operational system.
Identifying the right processes to automate, and designing automations that are built to last. Invest in the right automations first, avoid low-ROI tool deployments.
Building bots and workflows that execute structured, repeatable processes, reliably, at scale, without human involvement.
Adding intelligence to automation, handling the unstructured inputs, exception judgments and classification decisions that rules-based bots cannot.
Eliminating manual data movement between systems, so information flows automatically to where it's needed, when it's needed.
Keeping the automation estate reliable, improving and compliant, in production, over time. A patchwork of unmonitored bots is not an automation programme.
Infarsight's purpose-built automation accelerator — a configurable platform that orchestrates task-level automation across operational teams, with built-in monitoring, exception handling and human-in-the-loop controls.
Operational teams running TaskSight recover an average of 6 hours per person per day, redirected from manual task execution to operational performance.
Invoice, reconciliation and reporting processes that previously took hours are completed by bots in minutes, with higher accuracy and full audit trails.
Automation estates with active ops and governance programmes maintain near-zero silent failure rates, exceptions are caught, escalated and resolved before they impact operations.
Automated processes consistently deliver 3× the throughput of the manual equivalent, with consistent quality across 100% of volume.
From process audit to a governed, continuously improving automation estate.
Process audit, automation opportunity mapping, ROI scoring and phased roadmap. 1–2 weeks.
Architecture blueprint, automation design, exception path mapping, integration model. 2–3 weeks.
Bot development, integration delivery, AI augmentation where needed, UAT and sign-off. 4–8 weeks.
24/7 monitoring, exception management, SLA reporting and continuous improvement. Ongoing.
New process onboarding, estate scaling, AI capability expansion and quarterly ROI review. Continuous.
Also see: TaskSight accelerator → | Agentic AI — the decision layer above automation → | Data Engineering — what feeds the automation signals →
We start with a Process Audit & Automation Opportunity Assessment, mapping your highest-volume manual processes, scoring them for automation ROI and prioritising the first wave of delivery.
Infarsight Product Engineering builds, modernises and operates the software platforms that power enterprise operations, on Azure, AWS and modern cloud infrastructure. We measure engineering success in operational performance and uptime, not features shipped.
What is Enterprise Product Engineering?
Enterprise product engineering is the practice of designing, building and operating the software platforms that power business operations, not as standalone projects, but as embedded, continuously maintained systems. It combines architecture design, AI-accelerated development, reliability engineering and platform operations into a single accountable capability.
Every platform we build is designed to be operated, maintained and evolved. Reliability, observability and BAU ownership are part of the brief, not an afterthought.
Our engineers understand Travel, Ports and Mobility deeply. They build systems aligned to how operations work, not how a requirements document described them.
We don't hand over and leave. We embed into your teams and stay accountable for the systems we build, tracking their performance and evolving them as the business changes.
Our delivery accelerators connect directly to data, automation and agentic AI layers. Product Engineering isn't isolated, it's the execution layer of a broader operational system.
Designing platforms built for operational purpose, not just technical correctness. Systems that align to how operations actually work.
Moving legacy monoliths to scalable, maintainable architectures, without halting operations or gambling on a big-bang rewrite.
Designing systems that perform under operational pressure, and recover fast when they don't. Reliability is designed in, not tested in.
Keeping live systems healthy, stable and continuously improving, long after the delivery team has left.
Continuously improving live platforms so they grow with the business, without disruptive rebuilds. The alternative to incremental evolution is a costly rebuild every 3–4 years.
From requirements capture to production operations, AI is woven across the full SDLC, reducing effort, accelerating delivery and improving quality at every stage.
We choose what is right for your operational context, not what is convenient. Technology choices are made to serve the system's reliability and operational requirements.
Moving from big-bang project cycles to continuous delivery reduces time from idea to live feature by 60%.
Platforms redesigned with SRE principles consistently achieve 99.9%+ uptime on operationally critical workflows.
BAU stabilisation programmes reduce live incidents by up to 70% within two quarters of embedded engineering ownership.
Teams shipping from modernised, cloud-native architectures release 3× faster with significantly lower rollback rates.
From operational problem to production system, in a repeatable, governed process.
Platform & systems audit, stakeholder interviews, operational pain mapping, architecture assessment. 1–2 weeks.
Platform architecture, API contract design, data & integration model, reliability framework. 2–4 weeks.
Iterative engineering sprints, integration delivery, QA & test automation, performance testing. 6–16 weeks.
BAU support & monitoring, incident management, performance tuning, stakeholder reporting. Ongoing.
Backlog engineering, refactoring cycles, new capability delivery, architecture reviews. Continuous.
Also see: Agentic AI — the decision layer your platforms execute → | Data Engineering — what feeds your platforms → | Platform Ops & Governance →
We start with a Platform & Systems Assessment, mapping your current architecture, identifying reliability risks, modernisation opportunities and the highest-value engineering investments.
Infarsight Platform Ops & Governance is the foundation layer, it doesn't sit above data, AI or automation. It sits beneath all of them, enabling every capability to perform at the level the business requires.
What is Platform Operations and Governance?
Platform operations and governance is the ongoing engineering discipline of keeping cloud infrastructure, AI systems and data pipelines reliable, secure and cost-efficient in production. It covers observability, incident response, security compliance, FinOps and DevSecOps, ensuring the platforms enterprise operations run on maintain 99.9% uptime and remain auditable at all times.
Every capability built on the platform performs as designed, continuously, securely and at the scale operations demand.
We don't just keep servers running. We govern the full platform layer that data, AI and automation depend on, measuring success in capability uptime, not infrastructure availability.
Security, compliance, observability and FinOps governance are designed into every platform from day one. We have seen what happens when they are added after the fact, and we don't let it happen.
From infrastructure to data and AI platforms, we maintain constant visibility into health, performance, cost and compliance, ensuring issues are detected early and governance stays enforced.
Our Platform Ops practice connects directly to Data Engineering, Agentic AI, Intelligent Automation and Product Engineering. We govern the layer that makes all of them possible.
Designing and operating the cloud infrastructure that data pipelines, AI agents and automation platforms depend on, reliable, scalable and resilient.
Full-stack visibility across infrastructure, data pipelines, AI agents and automation, so issues are detected and resolved before they impact operations.
Keeping the platform secure, compliant and audit-ready, with governance designed in from the start, not retrofitted after an incident.
Keeping cloud spend aligned to business value, with visibility, accountability and continuous optimisation built into the platform operating model.
Building the developer platform, delivery pipelines and engineering standards that make every Infarsight capability faster, safer and more consistent to deploy.
Platforms governed with SRE principles consistently achieve 99.9%+ uptime on operationally critical workflows across data, AI and automation layers.
Full-stack observability means platform issues surface and are resolved before users or operational workflows are impacted.
ISO 27001, 9001 and 14001 certified. SOC 2 readiness. Governance designed from day one, not retrofitted after an incident or audit finding.
FinOps discipline keeps cloud costs visible and optimised. Waste eliminated continuously, not discovered at budget review.
From current-state assessment to a continuously governed, observable and secure platform estate.
Well-Architected Framework review, current-state audit, security posture assessment, FinOps baseline. 1–2 weeks.
Target architecture, observability framework, security controls design, FinOps governance model. 2–3 weeks.
IaC provisioning, observability tooling, CI/CD pipelines, security controls, FinOps tagging. 4–8 weeks.
24/7 monitoring, incident management, security governance, monthly FinOps review. Ongoing.
Cost rightsizing, platform evolution, new capability onboarding, quarterly governance review. Continuous.
Also see: Data Engineering — what runs on the platform → | Agentic AI — the agents the platform hosts → | Product Engineering — systems built to run on it →
We start with a Well-Architected Platform Assessment, reviewing your current infrastructure, observability gaps, security posture and FinOps baseline.
Deep integration capability across Travel, Hospitality and Mobility, connecting GDS, PMS, NDC, IoT, SCADA and every system in between through API-native, RPA and batch-driven patterns. Infarsight builds, monitors and maintains every integration.
What is Enterprise Integration Services?
Enterprise integration services connect the disparate systems, protocols and data sources that enterprise operations run on, GDS, PMS, ERP, IoT devices, SCADA systems and supplier APIs, into a single, observable data flow. For agentic AI and intelligent automation to work, the integration layer must be reliable, maintained and built to evolve. Infarsight treats integration as an engineering discipline, not a one-time project.
The intelligence layer is only as good as the data that feeds it. In Travel, Hospitality and Mobility, that data lives across dozens of systems, none of which were designed to talk to each other.
GDS APIs speak SOAP. NDC speaks XML. Hotel CRS systems use proprietary REST. Mobility infrastructure runs MQTT and SCADA protocols from a different era. A typical enterprise stack spans 15 or more distinct protocols.
A significant portion of supplier systems, particularly in hospitality and mid-market travel, offer no API. Data exists only in email inboxes, web portals, flat files and legacy databases. These gaps break automation unless addressed directly.
Amadeus releases API updates quarterly. Airlines pivot to NDC on their own schedule. IoT device firmware changes break data schemas. An integration built today must be maintained, monitored and adapted continuously, not just at build time.
Every integration starts with the best available API, REST, SOAP, GraphQL or gRPC. We implement to the full depth of the specification, not just the fields a UI exposes. Schema validation, error handling and retry logic are built in from day one.
Where no API exists, we do not stop. RPA-driven browser automation, SFTP batch file exchange, database direct-read and email parsing are all part of the toolkit, with the same observability standards applied as any API integration.
Every integration produces structured logs. Every API call is traced. Every failure is categorised, transient, permanent or schema-mismatch, and routed to the appropriate response. Integration health is monitored in real time, not discovered at incident time.
API versions change. Supplier systems are replaced. Data schemas drift. Every integration is versioned, documented and designed with a change-management path. Infarsight maintains integrations post-deployment, not just at build time.
Infarsight's integration capability spans the full technology stack of Travel, Hospitality and Mobility, from GDS transactions to shop-floor SCADA devices.
Infarsight integrates at full transactional depth with Amadeus, Sabre and Travelport, covering shopping, booking, ticketing, PNR lifecycle management, hotel, car and ancillary APIs. We also connect to NDC aggregators including Verteil, Duffel, AirGateway and TPConnects, and directly to major airline PSS platforms including Amadeus Altea and Navitaire.
Where no API exists, Infarsight deploys non-API integration patterns: RPA-driven browser automation using Playwright or Selenium, structured email parsing using NLP and template matching, SFTP and batch file exchange, flat file processing and database direct-read for legacy systems. The same observability standards apply regardless of the connectivity method, every integration is logged, traced and monitored.
Yes. Infarsight treats integration as an ongoing engineering discipline, not a delivery project. Post-deployment, we monitor all integrations in real time, tracking API latency, error rates and schema drift, and manage API version migrations, supplier system changes and schema evolution as part of a continuous maintenance engagement. SLA-aligned alerting is configured at deployment and maintained throughout the engagement.
We start with an integration assessment, mapping your systems, protocols and connectivity gaps across Travel, Hospitality and Mobility.
Infarsight is a Microsoft Solutions Partner, deploying Azure cloud infrastructure, Microsoft Fabric data platforms, Azure AI Foundry, Copilot integrations and Power Automate workflows for enterprise operations across Travel, Mobility and Logistics.
What is the Infarsight Microsoft Partnership?
Infarsight is a verified Microsoft Solutions Partner with active delivery capability across the full Microsoft cloud and AI stack. This partnership gives enterprise clients access to co-engineered solutions on Azure infrastructure, Microsoft Fabric data platforms, Copilot AI integrations and Power Automate workflow automation, all delivered by Infarsight's embedded engineering teams with Microsoft-verified expertise.
Cloud infrastructure, platform engineering and managed services on Azure, including AKS, Azure Functions, Azure Service Bus, Cosmos DB and Azure Monitor. Infarsight architects, deploys and operates Azure environments for enterprise operational systems in Travel, Mobility and Logistics.
End-to-end data platform on Microsoft Fabric, unifying data engineering, data science, real-time analytics and business intelligence in a single SaaS experience. Infarsight builds Fabric-based data foundations for operational intelligence programmes where Microsoft is the strategic data platform of choice.
Agentic AI and LLM-powered operational systems built on Azure AI Foundry, combining GPT-4o, Phi models and custom fine-tuned models with Infarsight's operational decision engineering. Used for travel disruption management, document intelligence, fleet dispatch reasoning and enterprise workflow automation.
Copilot integration and Copilot Studio custom agent development for enterprise operations teams. Infarsight builds domain-specific Copilot experiences, travel booking assistants, fleet dispatch copilots and port operations intelligence, embedded within Microsoft 365 and Teams workflows.
Intelligent automation programmes built on Power Automate, connecting Microsoft 365, Dynamics 365, Dataverse and enterprise operational systems through low-code workflow orchestration with AI augmentation. Infarsight's intelligent automation practice delivers 200+ automation programmes, many of which run on Power Platform as part of a broader Microsoft-first enterprise stack.
We start with a platform assessment, mapping your current Microsoft estate and identifying the highest-value Azure, Fabric and AI Foundry opportunities for your operations.
Infarsight deploys enterprise operational systems on AWS, using EC2, ECS, Lambda, S3, RDS, Kinesis and AWS IoT Core to build the cloud foundation that agentic AI and real-time data platforms require. Every deployment is architected for operational resilience, security and cost governance.
How Infarsight uses AWS
AWS is one of Infarsight's primary cloud delivery environments. Engineering teams deploy production operational systems, agentic AI pipelines, real-time data streaming, IoT ingestion and microservice architectures, on AWS infrastructure for clients who have standardised on Amazon cloud or require AWS-native services for compliance and data residency reasons.
Start with an AWS architecture review, we map your current estate and design the data, AI and integration layers your operations need.
Infarsight is a Google Cloud Partner, deploying BigQuery data warehouses, Vertex AI models, Pub/Sub streaming pipelines and GKE containerised workloads for enterprise operational intelligence programmes across Travel, Mobility and Logistics.
How Infarsight uses Google Cloud
Google Cloud is deployed by Infarsight primarily for data-intensive operational intelligence programmes where BigQuery's analytical performance, Vertex AI's managed ML infrastructure and Pub/Sub's real-time messaging capabilities align with client requirements. GKE provides the containerised runtime for microservice and agentic AI deployments on GCP.
Serverless analytics warehouse for operational reporting, historical analysis and real-time dashboard feeds. Infarsight builds BigQuery-based data foundations for clients requiring petabyte-scale analytics on Google Cloud, particularly for travel demand intelligence, fleet performance analytics and port throughput modelling.
Managed ML infrastructure and LLM access on Google Cloud. Infarsight uses Vertex AI for custom model training, deployment and serving in operational AI programmes, and Gemini API integration for agentic AI decision systems requiring Google's frontier model capabilities.
Real-time messaging and stream processing for operational data pipelines. Pub/Sub handles high-throughput event ingestion from travel booking systems, IoT devices and operational feeds. Dataflow processes and transforms streams at scale before landing in BigQuery or downstream AI systems.
Containerised application deployment and managed Kubernetes on Google Cloud. Infarsight deploys microservice architectures, agentic AI orchestration layers and operational APIs on GKE, with Cloud Run for serverless containerised workloads requiring rapid scaling.
Start with a GCP architecture assessment, we map your data, AI and infrastructure requirements and design the right solution stack.
Infarsight is a strategic engineering partner to Bosch Mobility Solutions (Bosch MPS), delivering data engineering, agentic AI and platform engineering capacity for connected vehicle, software-defined vehicle and automotive intelligence programmes globally.
About the Bosch MPS Partnership
Bosch Mobility Solutions (Bosch MPS) is one of the world's leading automotive technology companies. Infarsight is a strategic engineering partner, providing data engineering, agentic AI development and platform operations capacity that integrates with Bosch MPS's automotive technology stack. This partnership enables joint delivery of vehicle intelligence programmes for OEM clients requiring the combined depth of Bosch automotive expertise and Infarsight's operational AI engineering.
Engineering the data ingestion and streaming infrastructure for connected vehicle programmes, collecting CAN bus, OBD-II, GPS and ADAS sensor data from vehicle fleets, processing it in real time and making it available for AI and diagnostic applications.
ML models trained on vehicle telemetry to detect anomaly patterns in engine performance, brake systems and component wear, predicting faults before they occur and generating maintenance scheduling recommendations for fleet and OEM programmes.
Architecture and engineering support for software-defined vehicle (SDV) programmes, helping OEMs build the data platform, AI model layer and over-the-air update infrastructure that modern software-defined vehicles require. Delivered in partnership with Bosch MPS's automotive software expertise.
Operational AI systems for commercial vehicle fleet operators, integrating Bosch MPS telematics capabilities with Infarsight's AssetSight platform and predictive dispatch models to optimise vehicle utilisation, reduce fuel consumption and improve on-time delivery performance.
Fleet intelligence and connected vehicle programmes delivered for Volvo, Ashok Leyland, Eicher Motors and Royal Enfield, across telematics data platforms, predictive maintenance models and operational dispatch intelligence.
We work with automotive OEMs and fleet operators through our Bosch MPS partnership, combining automotive technology depth with operational AI engineering.
Zeliot is the developer of Condense — a real-time IoT and operational data streaming platform. Infarsight holds a minority investment in Zeliot and deploys Condense as the data foundation for mobility, fleet and logistics intelligence programmes requiring real-time telemetry at scale.
About Zeliot and Condense
Zeliot is a technology company specialising in IoT and real-time data streaming infrastructure. Condense is Zeliot's flagship platform, providing the data ingestion, processing and streaming capabilities that Infarsight uses as the data foundation for agentic AI and mobility intelligence programmes. Infarsight is a minority investor in Zeliot and a primary deployment partner for the Condense platform.
Zeliot develops infrastructure for real-time data collection, processing and streaming from IoT devices and operational systems. The company's flagship product, Condense — is purpose-built for the high-throughput, low-latency data demands of fleet telematics, connected vehicles and industrial IoT.
Infarsight's investment in Zeliot reflects a strategic alignment: the data layer that Condense provides is fundamental to the agentic AI and decision intelligence systems Infarsight builds for Mobility, Logistics and Travel clients.
We combine Zeliot's Condense platform with Infarsight's data engineering and operational AI expertise, giving you the full stack from device to decision.
Infarsight is an Optimizely Partner, implementing Optimizely's digital experience platform, content management and experimentation capabilities for enterprise clients in Travel, Hospitality and Enterprise Operations who require personalised, scalable digital experiences alongside their operational AI systems.
About the Optimizely Partnership
Optimizely is a leading digital experience platform used by enterprises to manage content, run A/B experimentation and deliver personalised digital experiences at scale. Infarsight's Optimizely partnership extends the company's product engineering and intelligent automation capability into the digital experience layer, helping clients connect their operational data and AI systems to the customer-facing digital platforms that Optimizely powers.
Optimizely CMS implementation and integration, structured content modelling, editorial workflow configuration, multi-site management and headless delivery for enterprise web properties.
Optimizely Web and Feature Experimentation, A/B testing, multivariate testing and feature flag management for travel booking flows, hospitality web experiences and enterprise digital products.
Optimizely Data Platform (ODP) integration, connecting operational customer data to Optimizely's personalisation engine to deliver relevant content and experiences based on booking history, travel preferences and operational context.
Headless and composable Optimizely deployments, connecting the content and experience layer to operational systems including booking engines, PMS, CRM and GDS via Infarsight's integration services practice.
Connecting Optimizely's digital experience layer to Infarsight's operational AI systems, surfacing real-time operational data (availability, pricing, disruption alerts) through the Optimizely platform to deliver context-aware digital experiences.
Ongoing Optimizely platform operations, performance monitoring, release management, content governance, platform upgrades and technical support as part of Infarsight's embedded platform operations model.
We implement Optimizely and integrate it with your operational data and AI systems, creating digital experiences driven by real-time operational intelligence.
We don't apply generic AI to industry problems. Infarsight embeds in the operational reality of Travel, Mobility and Logistics, with purpose-built agentic AI and automation for the specific systems, pressures and buyers of each segment.
Eight segments, one COE, from TMCs and DMCs managing corporate and destination operations, to Airlines running disruption management, Tour Operators fulfilling complex programmes and OTAs handling high-volume bookings. Travel-specific intelligence, not generic technology.
Fleet telematics, EV network intelligence, predictive dispatch, port operations and last-mile logistics, powered by Condense data engineering, AssetSight and a strategic partnership with Bosch Mobility Solutions for global programmes.
Our capability stack, Data Engineering, Agentic AI, Intelligent Automation and Product Engineering, applies to any operationally complex enterprise.
The travel industry is not a single market, it is eight distinct operational contexts, each with its own pressures, systems and buyers. Infarsight's Travel Center of Excellence brings together domain experts, engineering capacity and proprietary AI accelerators built for each segment. We don't apply generic technology to travel problems, we solve travel operations problems with travel-specific agentic AI and automation.
While customers expect seamless, instant outcomes, the teams delivering those outcomes are still switching between GDS, PMS, CRM, email and spreadsheets, filling integration gaps by hand.
What is Travel Operations AI?
Travel operations AI uses agentic systems to automate booking, post-booking, disruption management and coordination workflows across TMCs, airlines, hotels, DMCs, OTAs and tour operators. It connects GDS systems, PMS platforms, supplier APIs and operational tools into an automated decision layer, reducing manual processing, protecting revenue during disruptions and enabling operations teams to handle higher volumes without adding headcount.
Cancellations, delays, rebookings, hotel reassignments, every disruption triggers a chain of manual interventions that scale poorly, drive costs up and frustrate travellers.
GDS, PMS, CRM, ERP and supplier systems operate in silos. Data moves by email and spreadsheet. Every integration gap is filled by a person doing manual re-entry.
Yield decisions, resource allocation and service recovery all happen reactively, on reports that are hours old. The window for optimal action has already passed.
High-volume operators are adding headcount to manage complexity that technology should be handling. Operations grow linearly, automation hasn't kept up.
Thousands of interdependent decisions across flights, passengers, crew, gates and revenue, happening simultaneously, every hour. Infarsight connects flight ops, GDS, crew systems and ground handlers into a single real-time operational view with automated IRROPS resolution.
Corporate travel programmes, duty of care, GDS booking workflows and policy-compliant booking engines. Agents performing 172 clicks per request, spending 15–20 minutes per quote across GDS, email, CRM and ticketing systems. TripSight cuts that to one click.
Ground operations, airport transfers, excursion logistics and supplier coordination at destination. The issue isn't demand, the issue is that by the time a problem appears in a report, the opportunity to prevent it has already passed.
Multi-supplier package assembly, group travel operations, amendment processing and wholesale distribution. The data to prevent programme failures exists, it just isn't connected. Infarsight creates a programme intelligence layer across the entire tour operation.
Yield optimisation with real-time demand signals, housekeeping and maintenance task automation, group booking coordination and guest journey intelligence from pre-arrival through post-stay recovery.
Agentic AI for travel booking operations, automates requests from Email, Slack, Teams and WhatsApp. 172 clicks → 1 click. 23 minutes → 3.4 minutes per request.
Explore TripSight →Post-booking operations for DMCs and tour operators, supplier coordination, live flight sync, guide allocation and guest communications automated across complex programmes.
Explore JourneySight →Post-booking operations intelligence, orchestrates every task, handoff and exception across travel, hospitality and airlines. 6 hrs saved per operator daily. 95% SLA compliance.
Explore TaskSight →"Partnering with Infarsight has been a game changer for us. Their automation capabilities have not only streamlined our processes but also fuelled innovation, allowing us to bring new solutions to market faster than ever."
Anderson Hernandez — SVP Contact Centers & Operations, Hyatt Hotels & Resorts
AI for TMCs automates the high-volume, manual steps in corporate travel management: processing booking requests from email and messaging channels, checking policy compliance, querying GDS systems, managing post-booking exceptions and monitoring duty of care. TripSight reduces request-to-book turnaround from 23 minutes to 3.4 minutes. TMCs that deploy travel automation reduce cost-per-transaction while handling higher volumes without adding headcount.
For travel agencies and OTAs, agentic AI handles post-booking operations that scale poorly with volume: supplier confirmation monitoring, schedule change detection, IRROPS recovery, refund processing and customer communications. These processes are structured and repeatable, exactly the conditions where agentic systems outperform manual teams. TaskSight orchestrates this entire post-booking layer, reducing silent failure rates and freeing agents for the complex, relationship-intensive work that requires human judgement.
Infarsight integrates with Amadeus, Sabre and Travelport at full transactional depth, shopping, booking, ticketing, PNR lifecycle and ancillary services. NDC connectivity covers Level 3 and 4 across major airlines and aggregators including Verteil, Duffel and AirGateway. For hospitality, connectivity spans Opera, Mews, Synxis and major channel managers. The integration services practice maintains all connectivity post-deployment.
We begin with a Travel COE assessment, mapping your segment, systems and highest-value automation opportunities.
Airlines manage more simultaneous operational dependencies than virtually any other industry, flight operations, passenger management, crew scheduling, revenue, airports and regulatory compliance, all in real time. The question isn't whether to collect data. It's whether your teams can act on it fast enough.
What is Airline Operations Intelligence?
Airline operations intelligence uses agentic AI to connect flight operations, passenger management, crew scheduling, revenue management and ground coordination into a single decision layer. It detects disruptions before they escalate, evaluates recovery options automatically and executes rebooking, crew reassignment and gate coordination without manual intervention across each disconnected system.
Aircraft rotation, delays, maintenance holds, gate changes and airspace events cascade across the entire departure board. Infarsight builds the unified ops view that surfaces the cascade before it compounds.
Connections, overbooking, rebooking, loyalty status, accessibility needs and service recovery coordinated in minutes, not hours, with automated communications dispatched before passengers reach the gate.
Duty limits, certifications, positioning and standby coverage managed continuously across every flight in the network, with automated compliance checks preventing regulatory breaches before they occur.
Load factors, yield decisions, overbooking models and compensation exposure tracked against real-time operational events, every departure tracked against its cost model with live margin visibility.
Gate assignments, ground handlers, baggage systems and turnaround times connected, from flight ops, crew, catering and handling systems into a single operational view with automated alerts for every constraint.
Rules-based upsell and upgrade automation deployed across web, app and agent channels, triggered by the operational context of each passenger's journey, not scheduled marketing blasts.
IRROPS management agent automatically assesses disruption scope, identifies rebooking options, calculates the cost of each resolution path and rehouses passengers, before they reach the gate.
Flight ops, crew, catering, fuel and ground handling systems connected into a single operational view with automated alerts and sequenced task assignment across every concurrent departure.
Agentic AI for airline operations connects flight operations data, passenger management systems, crew scheduling and ground operations into a single intelligence layer, detecting disruptions, evaluating recovery options against operational constraints and executing rebooking, crew reassignment and gate coordination automatically. The goal is to reduce the time between disruption detection and passenger resolution from hours to minutes.
When a delay, cancellation or IRROP occurs, the system simultaneously evaluates: passenger connection risks and rebooking options across GDS and airline direct APIs; crew availability and regulatory constraints; gate and ground resource availability; and downstream fleet schedule impacts. Options are ranked against defined recovery priorities and either executed automatically or presented to operations controllers for confirmation, with full audit trail throughout.
Yes. Infarsight integrates with Amadeus Altea (Central Reservations, Inventory and Departure Control), Navitaire (LCC PSS), Radixx and SITA AMS. NDC Level 3 and 4 connectivity covers major network carriers and LCCs including Ryanair, EasyJet, IndiGo and AirAsia. The integration services practice maintains these connections and manages API version changes as carriers update their distribution systems.
We start with an airline operations audit, mapping your IRROPS workflow, disruption costs and highest-value automation opportunities.
The issue isn't demand, the issue is operational visibility. By the time a problem appears in a report, the opportunity to prevent it has already passed. Infarsight creates a programme intelligence layer across the entire destination operation, connecting flights, ground partners, suppliers, amendments and guest communications into a single view.
What is DMC Operations Automation?
Destination Management Company (DMC) operations automation uses agentic AI to coordinate ground operations, supplier confirmations, guide and vehicle allocation, live flight syncing and guest communications across concurrent programmes. It detects supplier failures, flight changes and programme exceptions before they reach guests, protecting programme profitability and client relationships.
A missed transfer. A double-booked room. A tour departure that left without a guest. By the time the operational failure surfaces, the financial and reputational cost has already been incurred. The operation responded, it just responded too late.
In tourism, operational failures are immediately visible. Guests don't write reviews about systems, they write reviews about their experience. A missed pickup, a late departure, a confusing collection point. The rating is permanent.
Tour operators build programmes around DMC reliability. One bad season, even one bad week at peak, triggers a commercial conversation. The trust that took years to build can be lost in a single disruption event that wasn't handled well.
AssetSight connects to live flight data feeds, vehicle dispatch adjusts automatically when flights are early, delayed or diverted. Guides and drivers notified automatically. The coordinator doesn't need to see the flight to dispatch correctly.
JourneySight orchestrates all supplier tasks, hotel confirmations, guide briefings, excursion logistics and amendment handling, across concurrent programmes simultaneously. No chasing emails. No status calls.
Arrival confirmations, transfer reminders, hotel check-in alerts and disruption notifications dispatched automatically via the guest's preferred channel, triggered by operational events, not manual sends.
Live vehicle health, driver locations, route adherence and ETA tracking across every transfer, with fuel efficiency analytics and driver performance scoring. 34% fuel reduction. Zero missed pickups target.
Live view of all active programmes, vehicles, drivers, guests and supplier status throughout the destination, with exception detection before problems become guest experiences.
Airline schedule changes, hotel stop-sells and ground partner reliability monitored continuously across every active departure, with automated amendment processing and passenger impact assessment before your team is even alerted.
TripSight monitors flight schedules, hotel confirmations and ground partner status from booking confirmation. Any change triggers immediate impact assessment.
AssetSight auto-dispatches from actual landing time. Live vehicle tracking, guest notification and airport collection automated without coordinator intervention.
JourneySight orchestrates excursion logistics, guide assignments, supplier confirmations and hotel coordination across every active programme simultaneously.
Disruptions detected before guests feel them. Automated resolution for routine exceptions, complex cases escalated with full context and recommended action.
Transfer to airport automated. Every disruption event, resolution cost and guest impact captured automatically for per-departure performance reporting.
We begin with a destination operations audit, mapping your current transfer workflows, supplier coordination overhead and highest-cost operational failures.
Fleet telematics, EV charging network management, predictive maintenance, port terminal intelligence and last-mile logistics, powered by Condense real-time data engineering, AssetSight and a strategic partnership with Bosch Mobility Solutions for global automotive and mobility programmes. We don't treat mobility as a side practice, Infarsight's Mobility COE is a dedicated capability unit built for the operational complexity of fleets, ports and intelligent transport.
What is Mobility Operations Intelligence?
Mobility operations intelligence applies agentic AI and real-time data engineering to fleet management, EV charging networks, last-mile logistics and connected vehicle programmes. It connects telemetry, dispatch systems, IoT infrastructure and operational data into a unified intelligence layer, enabling predictive maintenance, route optimisation, port terminal coordination and vehicle health monitoring at enterprise scale.
Predictive dispatch based on live vehicle health, location and availability. Fleet health scoring, maintenance prediction and route optimisation across conventional and EV fleets, powered by AssetSight and Condense telemetry pipelines.
Charging network state management, real-time availability, session monitoring, demand forecasting, fault detection and battery health degradation tracking across distributed EV infrastructure. Charging schedules optimised against operational demand and grid costs.
Berth scheduling, gate operations, container dwell time reduction and port command centers, connected across vessel tracking, equipment sensors, gate systems and ERP platforms. Built with Bosch MPS for complex port intelligence programmes.
AI-driven route optimisation, delivery sequence automation, real-time exception handling and customer notification for last-mile operations. Connected vehicle intelligence and predictive quality systems for OEM vehicle intelligence programmes.
Infarsight is a strategic technology partner for Bosch Mobility Platform and Solutions, delivering data engineering, agentic AI and operational intelligence for Bosch's global mobility programmes across fleet management, port operations, last-mile logistics and EV infrastructure.
bosch-mps.com ↗Continuous intelligence across fleets, vehicles and infrastructure, using telemetry, anomaly detection and predictive signals so failures are detected before they impact operations. From IoT ingestion to automated maintenance dispatch in one connected system.
AI for fleet operations uses real-time telemetry and machine learning to optimise dispatch decisions, predict vehicle faults before breakdown, monitor driver behaviour and reduce fuel consumption. Unlike scheduling software that plans routes at the start of a shift, fleet operations AI re-optimises continuously, adjusting assignments as vehicle health changes, traffic conditions shift and delivery priorities update throughout the day. Infarsight clients achieve up to 34% fuel reduction and 97% on-time dispatch reliability.
Agentic AI for ports uses real-time vessel AIS data, berth constraints, yard capacity and equipment availability to optimise berth allocation, container staging and gate throughput continuously, not just at the start of each shift. When a vessel runs late, the system automatically re-sequences berth allocation and yard operations to minimise the cascade of delays. Reference clients include Ports America and Adani Ports and Logistics.
Bosch Mobility Solutions (Bosch MPS) is Infarsight's strategic technology partner for connected vehicle and software-defined vehicle programmes. Through this partnership, Infarsight provides data engineering, agentic AI and platform engineering capacity for automotive OEM programmes globally, extending Infarsight's mobility capability into vehicle intelligence, ADAS data platforms and connected car programmes for Bosch's automotive client base.
We begin with a Mobility COE assessment, mapping your fleet telemetry coverage, operational gaps and highest-value automation opportunities.
Sanjeev Sethi — Founder & CEO, Infarsight
Founded in 2014 in Princeton, New Jersey, Infarsight is a global agentic AI and enterprise automation company. We connect enterprise systems with AI to run operations faster and protect revenue, across Travel, Mobility, Logistics and Ports. From airline operations to port terminals, we partner with enterprises to replace reactive, manual processes with automated decision systems.
Our model is not advisory, we embed engineers, build production AI systems and stay accountable for the outcomes those systems deliver. We design, build and operate agentic AI, data engineering and intelligent automation solutions that make enterprise operations faster, more precise and more profitable. We measure success in decisions automated, revenue protected and operational hours returned to the teams we work with.
Princeton, New Jersey — Infarsight Ideation Inc. established
First Travel practice and enterprise clients. TripSight concept begins.
Strategic investment and regional expansion into the Middle East
200+ automation programmes launched across Travel, Hospitality and Ports
Data Engineering formalised as a core capability line
Ports & Logistics practice launched. Adani Ports and Ports America engaged.
Agentic AI and ML formalised. LLM-powered operational agents in production.
Middle East HQ opened in Dubai. Regional delivery footprint expanded.
Condense, TripSight, TaskSight and AssetSight released as deployable products
CommandSight and DecisionSight released. Bosch MPS strategic partnership formalised.
USA · UAE · India. Seven-plus year average client tenure. Built on trust and long-term partnerships, not project handovers.
Engineering, talent and proprietary accelerators: TripSight, TaskSight, AssetSight. Plus minority investment in Condense, the Zeliot real-time data platform.
Client satisfaction measured and reported. 85% employee retention. Two of the hardest numbers to maintain simultaneously.
Not a startup still finding product-market fit. A decade of operational delivery across Travel, Mobility, Ports and Logistics.
We don't deliver and disappear. Infarsight engineers embed directly into operational teams, attend standups, own systems and ship alongside clients every day. We stay accountable for the performance of what we build.
Travel, Mobility and Logistics are not use cases for us, they are the industries we were built to serve. Our templates encode operational intelligence that took a decade to accumulate. We know where the exceptions live before you describe them.
Our five engineering practices, Data Engineering, Agentic AI, Intelligent Automation, Product Engineering and Platform Operations, are designed to work together. The full stack is the product. Isolated capabilities are only valuable when connected.
Operational audit, system mapping and opportunity sizing. We identify the highest-value automation gaps and their cost. 1–2 weeks.
Architecture blueprint, workflow design, integration model and MVP scoping. System design aligned to operational context, not technical preference. 2–4 weeks.
Iterative engineering sprints, integration delivery, QA, performance testing and UAT. Embedded team, accountable outcomes. 4–16 weeks.
Live monitoring, incident management, performance tuning and team enablement. We stay in the system we built. Ongoing.
Workflow expansion, AI layer activation, new use cases and quarterly business reviews. Continuous improvement from measured operational outcomes. Continuous.
"Partnering with Infarsight has been a game changer for us. Their automation capabilities have not only streamlined our processes but also fuelled innovation, allowing us to bring new solutions to market faster than ever. Their approach has truly accelerated our digital transformation, driving both efficiency and growth."
Anderson Hernandez — SVP Contact Centers & Operations, Hyatt Hotels & Resorts
Infarsight engineers agentic AI systems, data engineering platforms, intelligent automation and enterprise integration services for operationally complex enterprises across Travel, Mobility and Logistics. The company embeds engineers directly into client operations and stays accountable for the systems it builds, measured in decisions automated, revenue protected and operational hours returned to the teams it works with. Founded in 2014, headquartered in Princeton, New Jersey.
Infarsight does not deliver recommendations or hand over at go-live. Engineers embed into client operational teams, attend standups, own the systems they build and are measured by the operational outcomes those systems deliver. The five engineering practices, data engineering, agentic AI, intelligent automation, product engineering and platform operations, are designed to work as a connected stack. The average client tenure is seven years. The company holds a 91.2 Net Promoter Score.
Infarsight Ideation Inc. is headquartered at Suite 300, 5 Independence Way, Princeton, New Jersey 08540. Regional offices operate in Dubai, UAE and India, where the Mobility Center of Excellence is based. The company serves clients across North America, the Middle East, Europe and Asia-Pacific. Contact: info@infarsight.com and +1 865 424 0205.
We start with an operational assessment, mapping your systems, identifying decision gaps and designing the architecture that connects data, decisions and outcomes.
We map your systems, identify the highest-value agentic AI and automation opportunities and design the architecture that connects data engineering, decision intelligence and operational execution. No obligation, just operational clarity.
We respond within 24 business hours. No spam, no sales pressure.
We map your systems, data flows and processes, identifying decision delays, integration gaps and their operational cost. 1–2 hour conversation, no preparation needed.
We design the data-to-decisions architecture for your specific gaps, covering integration points, automation logic, AI layer and platform requirements with realistic effort and timeline.
We scope a focused pilot, fast time-to-value with minimal risk. You see the system working in your environment before a long-term commitment is required.
Infarsight operates from Princeton, Dubai and India — giving clients proximity to commercial leadership in the USA and UAE, and engineering depth from India.
Suite 300, 5 Independence Way
Princeton, NJ 08540
Dubai · United Arab Emirates
Mobility COE · Engineering Centre
We don't believe in one-size-fits-all technology delivery. Each engineering practice is purpose-built for the operational context it serves, with embedded teams, accountable outcomes and long-term ownership of the systems and data quality we deliver.
Traditional IT delivery was built for a different era, scoped deliverables, measured in features shipped, handed off at go-live. We build operational systems: continuous intelligence that evolves, measured in decisions automated and outcomes achieved.
Automated decision routing eliminates waiting for manual reviews, reports and approval chains.
End-to-end workflow automation collapses turnaround time for key operational processes.
Intelligent routing ensures exceptions reach humans only when human judgment is required.
Condense accelerator reduces time to production-grade data pipelines vs building from scratch.
Start with an operational assessment, we map your systems and identify the highest-value entry point.
Infarsight is a global AI operations technology company. We connect enterprise systems with AI to run operations faster and protect revenue, embedding engineers, building production systems and staying accountable for the outcomes those systems deliver.
Infarsight was founded in 2014 in Princeton, New Jersey with a single conviction: the gap between enterprise data and operational decisions was costing businesses far more than they realised, in revenue lost to slow responses, in costs accumulated through reactive operations, and in teams burning capacity on work that technology should be doing.
We started by building intelligent automation programmes for travel and hospitality enterprises, embedding engineers directly into operational teams, learning where the exceptions live, understanding how operations actually work versus how requirements documents describe them. Over a decade, we expanded across Mobility, Ports and Logistics, developed proprietary delivery accelerators, invested in platform companies and built two industry Centers of Excellence.
Today we architect and deploy Agentic AI systems that connect existing enterprise systems, helping operations, data and engineering teams detect issues faster, make timely decisions at scale and run without the manual coordination overhead that constrains growth.
"We lead with data, act with purpose, build with scale in mind."
Sanjeev Sethi — Founder & CEO, Infarsight
Princeton, New Jersey — Infarsight Ideation Inc. established with a focus on intelligent automation for enterprise operations.
First Travel practice and enterprise clients. Embedded in TMC and DMC operations across the Middle East and North America.
Strategic investment and expansion across the GCC region. Travel operations programmes scale across Saudi Arabia and UAE.
200+ automation programmes launched. UiPath, Power Automate and Appian practices formalised across Travel, Hospitality and Ports.
Databricks and Microsoft Fabric partnerships established. Condense data platform concept begins.
Ports & Logistics practice launched. Adani Ports & Logistics and Ports America engaged as flagship clients.
LLM-powered operational agents in production. Decision Intelligence and Digital Twin programmes formalised.
Middle East HQ opened in Dubai. Regional delivery footprint expanded to support GCC-based enterprise clients.
Condense, TripSight, TaskSight and AssetSight released as deployable products. TripSight 3.0 launched at tripsight.ai.
CommandSight and DecisionSight released. Bosch MPS strategic partnership formalised for global mobility programmes.
When you need engineering depth inside your ops team. Infarsight engineers attend your standups, own your systems and ship alongside your team, every day. Not a vendor, a member of the team.
When you need a dedicated engineering capability unit. A fully managed CoE, engineers, architects and QA, running long-term platform programmes with full governance, documentation and knowledge transfer.
When you need a defined result, not a team on retainer. Fixed-scope engagements with defined outcomes, we own the system, the quality and the operational result. Measured in decisions automated and outcomes achieved.
"Partnering with Infarsight has been a game changer for us. Their automation capabilities have not only streamlined our processes but also fuelled innovation, allowing us to bring new solutions to market faster than ever. Their approach has truly accelerated our digital transformation, driving both efficiency and growth."
Anderson Hernandez — SVP Contact Centers & Operations, Hyatt Hotels & Resorts · 91.2 NPS
We begin with an Operational Intelligence Assessment, mapping your systems, identifying decision gaps and designing the architecture that connects data, decisions and outcomes.
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120+ engineers, three continents, one mission — make enterprise operations intelligent. We work on real systems that handle millions of decisions for airlines, ports, fleets and travel companies every day.
You will work on production AI systems that handle millions of decisions across airlines, ports, fleets and enterprise operations. When your agent resolves a travel disruption in 90 seconds, a real person makes their flight.
We are architecture-led. Engineers own delivery from data infrastructure through agentic AI systems to production operations. You don't hand off at go-live — you stay accountable for what you build.
With 7+ year average client tenure, you build genuine expertise in Travel, Mobility or Logistics — not just engineering in the abstract. You understand the domain, the systems and the operators who depend on them.
Most roles are fully remote or hybrid. We have offices in Princeton NJ, Dubai and India — but we judge on outcomes, not office attendance. You work where you do your best engineering.
You will work alongside engineers in three time zones, with partners at Bosch, Microsoft and Databricks. Infarsight's client work puts you inside Hyatt, Ports America, Volvo and Amadeus — not at arm's length.
Agentic AI is moving fast. We invest in learning — internal knowledge sharing, partner certifications (Microsoft, Databricks), and the natural education that comes from working on genuinely hard engineering problems.
All roles are open to remote or hybrid candidates unless otherwise stated. We are building across every engineering practice simultaneously.
Practical frameworks, engineering insights and operational research from Infarsight — covering Agentic AI, Data Engineering, Decision Intelligence, Travel Automation and Mobility Operations.
Topics covered in Infarsight Insights
We're publishing our thinking on Agentic AI, Decision Intelligence and operational transformation. Stay updated.
Everything you need to know about agentic AI for enterprise operations — Travel, Mobility, Logistics, Ports and beyond.
Agentic AI for enterprise operations refers to AI systems that autonomously monitor operational signals, evaluate options against business constraints and execute decisions across connected enterprise systems — without requiring manual intervention for each step.
Unlike reporting tools or dashboards that surface insights for humans to act on, agentic systems close the loop automatically: rerouting logistics, resolving booking exceptions, reallocating fleet assets, adjusting berth schedules and escalating only the decisions that genuinely require human judgement.
Infarsight builds agentic AI systems across three domains: Travel and Hospitality, Mobility and Transportation, and Logistics and Ports. Every system is built on a connected stack — data engineering provides the operational signals, agentic AI evaluates and decides, and product engineering platforms execute the action.
Standard AI and machine learning systems produce predictions or recommendations — they tell you what is likely to happen or what action to consider. A human still has to read the output and decide what to do. Agentic AI goes further: it perceives the current operational state, reasons about the options, selects an action and executes it across connected systems automatically.
The distinction matters in operations. When a vessel ETA shifts by 38 minutes, a predictive model will flag the disruption. An agentic AI system will re-optimise berth allocation, reschedule yard operations, notify the relevant terminal teams and update the port management system — all within seconds and without a human in the loop for each step.
Infarsight builds agentic systems that are production-grade, not demos. All agents are auditable, have defined escalation paths and operate within business-defined constraint boundaries.
Decision intelligence is the capability layer that sits between operational data and automated action. It encompasses signal detection (identifying when something requires a decision), option generation (evaluating possible responses against constraints), decision selection (choosing the optimal action based on defined priorities) and execution routing (triggering the action in the relevant system).
Agentic AI is the implementation of decision intelligence at scale. Infarsight's DecisionSight accelerator provides the pre-built decision intelligence framework — signal models, constraint libraries, scenario simulation and escalation routing — that can be configured for Travel, Logistics, Ports and Fleet operations without rebuilding from scratch.
Every engagement begins with an operational assessment — Infarsight engineers map your current systems, identify the decision points where automation would deliver the highest value and quantify the operational and commercial impact. This is not a consulting exercise; it produces a specific engineering blueprint.
From there, Infarsight embeds engineers directly into your operational environment, builds the data foundation, constructs and tests the agents in your actual systems and remains accountable for production performance. Typical time to first agent in production ranges from 6 to 12 weeks depending on data readiness. Infarsight does not hand over at go-live — embedded teams continue to operate and improve the systems post-deployment.
Corporate travel automation uses agentic AI to handle the end-to-end processing of offline travel requests — the requests that arrive via email, Slack, Microsoft Teams or WhatsApp and currently require an agent to manually query a GDS, check policy compliance, build an itinerary and confirm the booking.
Infarsight TripSight automates this entire sequence. When a request arrives, TripSight parses the intent, queries Amadeus, Sabre or Travelport GDS systems, checks the traveller's policy profile, generates compliant itinerary options and either confirms automatically or routes for approval — all without manual agent involvement. Request-to-book turnaround reduces from 23 minutes to 3.4 minutes. Agent clicks per request reduce from 172 to 1.
TripSight is deployed for TMCs handling high volumes of corporate offline requests, corporate travel departments and OTAs managing complex multi-segment itineraries.
IRROPS (irregular operations) are the flight delays, cancellations, misconnections and crew disruptions that cascade through travel itineraries. Standard industry processing involves agents manually identifying affected passengers, querying available alternatives, evaluating policy constraints and executing rebookings — a process that averages 30 or more minutes per disruption event at scale.
Travel disruption management automation uses agentic AI to detect IRROPS events in real time from airline data feeds, evaluate rebooking options against passenger tier, policy and availability, execute the optimal rebooking automatically and notify affected passengers — completing the entire loop in under 2 minutes.
Infarsight's Decision Intelligence platform handles IRROPS automation for airlines, TMCs and DMCs. It integrates with GDS systems (Amadeus, Sabre, Travelport), airline APIs and NDC channels to access live inventory during disruption resolution.
Infarsight serves eight travel segments with purpose-built agentic AI and engineering capability:
Reference travel clients include Hyatt Hotels and Resorts, Trisept Solutions, Amadeus and multiple undisclosed TMCs and airline programmes.
Infarsight integrates with all three major Global Distribution Systems: Amadeus, Sabre and Travelport. Integration patterns include GDS querying for availability and pricing, PNR creation and modification, ticketing, refunds and schedule change handling.
Beyond GDS, Infarsight also integrates with NDC (New Distribution Capability) airline APIs, hotel property management systems (Opera, Mews, Cloudbeds), car rental systems and ground operator platforms. All integrations are built to be observable, retry-safe and auditable — critical requirements for operational travel systems where a failed integration has direct passenger impact.
AI for port terminal operations applies real-time data intelligence and agentic decision-making to the physical and logistical complexity of port operations — berth allocation, container yard management, equipment deployment, gate throughput and vessel scheduling.
Traditional port operations rely on planners manually reconciling vessel ETAs, berth capacity, yard state and equipment availability. When a vessel ETA shifts by 38 minutes, the downstream re-planning — berth reallocation, yard restaging, crane resequencing — can take hours and still leave sub-optimal outcomes.
Infarsight's port operations AI ingests live AIS vessel tracking, berth constraint data, yard sensor feeds and equipment telemetry to continuously optimise allocation decisions. When ETAs change, the system re-optimises the entire berth schedule and yard plan automatically in under 10 seconds. This reduces demurrage by up to 30% and accelerates cargo turnaround by up to 25%. Infarsight has deployed port operations AI for Ports America and Adani Ports and Logistics.
Berth scheduling AI uses real-time vessel AIS data, tide windows, berth dimensions, crane availability and yard capacity to continuously optimise the sequence and timing of vessel berthing. Unlike static scheduling systems that create a plan at the start of the day, AI-driven berth scheduling recalculates continuously as conditions change.
Demurrage — the cost incurred when a vessel waits beyond its contracted berth window — is directly caused by scheduling failures: vessels arriving to find their berth occupied, equipment not ready or yard blocks not cleared. AI berth scheduling eliminates the manual re-planning delays that allow these situations to develop, ensuring the physical operation is always aligned to the live vessel schedule.
Infarsight's berth scheduling AI delivers up to 30% reduction in demurrage costs and up to 99% cargo SLA compliance for tier-1 port terminal operators.
A digital twin for port operations is a continuously updated virtual replica of the physical terminal — live berth positions, container yard state, equipment locations, gate throughput and vessel queue — that updates in real time from operational data feeds. It is the single source of operational truth for the terminal.
The digital twin serves two roles simultaneously: it provides operational visibility (every planner sees the same live picture of the terminal state) and it is the data foundation that agentic AI systems use to reason about optimisation decisions. You cannot build reliable port AI without a reliable digital twin underneath it.
Infarsight builds port digital twins using live data from AIS feeds, terminal operating systems, IoT sensors and equipment telemetry, delivered through the Condense real-time data platform. The twin underpins all downstream agentic applications — berth scheduling, yard optimisation, anomaly detection and SLA monitoring.
Fleet operations AI uses real-time telematics, predictive models and agentic decision-making to automate and optimise the core decisions in fleet management: dispatch, routing, maintenance scheduling, fuel management and driver behaviour monitoring.
Unlike traditional fleet management systems that report on what has happened, fleet operations AI acts on what is happening — detecting a vehicle health anomaly before it becomes a breakdown, reassigning a route when traffic patterns shift, scheduling preventive maintenance at the optimal moment to minimise downtime and rerouting deliveries when a vehicle is removed from service.
Infarsight's AssetSight platform delivers fleet operations AI across commercial fleets, logistics operators and automotive OEM after-sales programmes. Outcomes include 34% fuel reduction, 97% on-time dispatch reliability and up to 16% higher fleet utilisation. Deployed for Volvo, Ashok Leyland, Eicher and Royal Enfield.
Predictive vehicle maintenance AI analyses real-time telemetry from vehicle sensors and CAN bus data to detect anomalies in engine behaviour, transmission, braking systems and electrical components — identifying developing faults 24 to 72 hours before they result in breakdown or failure.
The commercial value is significant: unplanned breakdown in a commercial fleet costs 2 to 3 times more than scheduled maintenance, and vehicle downtime in fleet-dependent operations directly translates to missed deliveries, failed SLAs and compensation costs. Predictive maintenance converts unplanned events into scheduled maintenance windows.
Infarsight builds predictive maintenance systems on top of real-time telematics data pipelines, using anomaly detection models trained on vehicle-specific fault signatures. The Condense platform by Zeliot provides the real-time IoT data ingestion layer that feeds these models with continuous vehicle data at scale.
EV fleet intelligence applies real-time data and AI to the specific operational challenges of electric vehicle fleets: charging demand forecasting, charger health monitoring, battery state of charge tracking, range anxiety mitigation and charge scheduling optimisation.
Managing an EV fleet introduces constraints that do not exist in ICE fleets — charging availability, charging time windows, battery degradation curves and grid demand pricing all interact to make dispatch and route planning significantly more complex. EV fleet intelligence systems optimise across all of these constraints simultaneously.
Infarsight works with automotive OEMs and fleet operators on EV intelligence programmes through its Bosch Mobility Solutions partnership and its Mobility Centre of Excellence in India. The Condense real-time data platform from Zeliot provides the IoT telemetry foundation for EV charging network monitoring and battery analytics.
Infarsight is a strategic engineering partner to Bosch Mobility Solutions (MPS) — the Bosch division responsible for connected vehicle systems, software-defined vehicle platforms and automotive software engineering. The partnership gives Infarsight clients access to Bosch's automotive technology ecosystem, including L-OS (Logistics OS), D-OS (Driver OS) and EV-OS platform components.
For mobility and automotive OEM clients, this means Infarsight can deliver AI, data engineering and software engineering that is natively integrated with Bosch's vehicle software platforms — without the complexity of bridging between incompatible technology stacks. Infarsight provides the data layer, AI layer and software engineering; Bosch provides the vehicle software platform.
Active Bosch partnership engagements include connected vehicle programmes for major OEMs and fleet intelligence deployments across the Indian subcontinent and Europe.
Infarsight data engineering services span seven practice tracks, all oriented toward making operational data decision-ready in real time:
All programmes use embedded engineers who remain accountable for data quality and platform performance after go-live — Infarsight does not hand over and walk away.
Basic RPA automates deterministic, rule-based steps in a single system. It breaks the moment an exception occurs or a screen layout changes. Infarsight's intelligent automation adds an AI layer that handles unstructured inputs, makes contextual decisions and orchestrates workflows across multiple enterprise systems simultaneously.
Where RPA routes an exception to a human queue, AI-augmented automation detects the exception pattern, evaluates resolution options, selects the appropriate action and either resolves it automatically or escalates with full context attached — dramatically reducing the number of exceptions that actually reach a human agent.
Infarsight has delivered 200+ intelligent automation programmes across Travel, Ports, Mobility and Airlines on Microsoft Power Automate, Appian and ServiceNow. Enterprise integration is handled by Infarsight's dedicated Integration practice, which covers GDS, NDC, PMS, IoT, SCADA and API patterns across 50+ integration templates.
Condense is the real-time IoT and operational data streaming platform built by Zeliot, a company in which Infarsight holds a minority investment. It provides the data foundation layer for Infarsight's Mobility, Fleet and Logistics engineering programmes.
Agentic AI systems require continuous, clean, contextualised operational data to perceive, reason and act correctly. Without a reliable real-time data layer, agents operate on stale or incomplete information — producing decisions that are correct for a state that no longer exists. Condense ensures that the data flowing into Infarsight's AI agents is current, connected and contextual.
Condense is not positioned as a standalone competing platform. It is embedded as a "Powered by Condense" delivery accelerator within Infarsight engineering engagements, reducing pipeline build time and improving operational data quality from day one of deployment.
Three differences separate Infarsight from standard IT services and consulting firms.
Domain depth over generic delivery. Infarsight operates in Travel, Mobility and Logistics — not every industry. This means the engineering team already understands the operational context, the systems landscape, the integration patterns and the failure modes before the engagement begins. Generic IT firms learn your industry on your time and budget.
Embedded accountability, not handover. Infarsight engineers embed directly into client operations and remain accountable for the systems they build — monitoring, operating and improving them post go-live. The commercial model is built around outcomes, not deliverables. Infarsight measures success in decisions automated, revenue protected and operational hours returned.
A connected stack, not isolated capabilities. Data Engineering, Agentic AI, Intelligent Automation, Product Engineering, Platform Operations and Integration are designed to work together. Clients do not have to integrate outputs from six different vendors — one engineering partner owns the complete operational intelligence stack. 91.2 NPS from 30+ enterprise clients across three continents.
Infarsight has delivered programmes for 30+ enterprise clients across North America, the Middle East, Europe and Asia-Pacific. Reference clients include:
Infarsight holds a 91.2 Net Promoter Score and 85% employee retention rate — both independently measured indicators of delivery accountability and team stability.
Infarsight Ideation Inc. is headquartered in Princeton, New Jersey, USA (Suite 300, 5 Independence Way, Princeton NJ 08540). The company operates regional offices in Dubai, UAE and India, where the Mobility Centre of Excellence — a 50+ person team focused on Fleet, EV and Automotive AI — is based.
Infarsight serves clients across North America, the Middle East, Europe and Asia-Pacific. Contact the team at info@infarsight.com or +1 865 424 0205.
Every engagement begins with an Operational Intelligence Assessment — a structured conversation where Infarsight engineers map your current systems and operational environment, identify the decisions being made manually that AI could handle and quantify the potential commercial impact. This assessment is not a sales pitch. It produces a specific engineering recommendation and an honest view of where agentic AI would and would not add value in your operations.
To request an assessment, contact the team directly at info@infarsight.com or book through the contact page.
Have a question that is not answered here?
Talk directly with an Infarsight engineer about your operational context.
Build and own real-time data pipelines that power agentic AI decision systems across Travel, Mobility and Logistics operations.
You will architect and operate production-grade data pipelines for enterprises where data latency directly translates into operational cost. Your pipelines feed Infarsight's agentic AI agents — fleet dispatch, port berth scheduling, travel disruption resolution — in real time.
Share your CV and a brief note on why this role and why now. We read every application.
Design and ship multi-agent AI systems that autonomously resolve operational disruptions without manual intervention.
This is not a prompt engineering role. You will build production agentic systems that perceive operational state, reason under constraints and execute decisions across live enterprise systems. Agents you build will close travel disruptions in under 2 minutes, reallocate fleet assets in real time and re-sequence port berth plans when vessel ETAs shift.
Share your CV and a brief note on why this role and why now. We read every application.
Own the technical architecture for Infarsight's Travel Centre of Excellence across GDS, PMS, NDC and airline systems.
You will be the architectural authority for Infarsight's travel technology stack, working directly with TMCs, airlines, DMCs and OTA clients to translate operational requirements into scalable integration and AI architectures.
Share your CV and a brief note on why this role and why now. We read every application.
Own the reliability, security and observability of Infarsight's production platforms across Azure, AWS and GCP.
Infarsight runs production AI systems for enterprises where platform downtime means missed flights, delayed shipments and unresolved disruptions. You will be the engineering guardian of that uptime.
Share your CV and a brief note on why this role and why now. We read every application.
Lead AI-augmented automation programmes across Travel, Ports and Mobility — moving beyond RPA into multi-system orchestration.
You will own the intelligent automation practice for client engagements where process complexity and exception volume make standard RPA insufficient.
Share your CV and a brief note on why this role and why now. We read every application.
Build and maintain deep Amadeus GDS integrations — shopping, booking, ticketing, disruption handling and NDC — for enterprise travel automation.
Infarsight is building agentic AI systems that operate directly inside Amadeus. You will build the integration layer that connects TripSight and our decision intelligence systems to Amadeus APIs with enterprise-grade reliability.
Share your CV and a brief note on why this role and why now. We read every application.
Own Sabre GDS integrations across air, hotel and car — enabling TripSight to operate reliably inside Sabre's booking ecosystem.
Infarsight's TripSight platform automates corporate travel booking inside Sabre for TMC and OTA clients. You will build the integration layer that makes that work at production scale.
Share your CV and a brief note on why this role and why now. We read every application.
Define Infarsight's engineering architecture across data, agentic AI and product engineering — setting the technical direction that 120+ engineers execute against.
As Principal Architect, you will own the technical vision for how Infarsight builds. You will define reference architectures across six engineering practices, establish engineering standards, lead pre-sales for complex engagements and be the technical authority that clients trust and engineers respect.
Share your CV and a brief note on why this role and why now. We read every application.
Build the interfaces and APIs that make Infarsight's operational AI visible and actionable — dashboards, command centers and workflow tools.
This is a role for a developer who wants to grow fast in a real production environment. You will build full-stack features for TripSight, TaskSight and CommandSight, working alongside senior engineers who take mentorship seriously. You will ship to production in your first month.
Share your CV and a brief note on why this role and why now. We read every application.
We read every application personally. Complete this form and we will be in touch within 5 business days. Please reply to your confirmation email with your CV attached.
After submitting, you will receive a confirmation email. Please reply to it with your CV attached as a PDF. We keep all applications confidential and do not share your details externally.
We read every application personally. Complete this form and we will be in touch within 5 business days. Please reply to your confirmation email with your CV attached.
After submitting, you will receive a confirmation email. Please reply to it with your CV attached as a PDF. We keep all applications confidential and do not share your details externally.
We read every application personally. Complete this form and we will be in touch within 5 business days. Please reply to your confirmation email with your CV attached.
After submitting, you will receive a confirmation email. Please reply to it with your CV attached as a PDF. We keep all applications confidential and do not share your details externally.
We read every application personally. Complete this form and we will be in touch within 5 business days. Please reply to your confirmation email with your CV attached.
After submitting, you will receive a confirmation email. Please reply to it with your CV attached as a PDF. We keep all applications confidential and do not share your details externally.
We read every application personally. Complete this form and we will be in touch within 5 business days. Please reply to your confirmation email with your CV attached.
After submitting, you will receive a confirmation email. Please reply to it with your CV attached as a PDF. We keep all applications confidential and do not share your details externally.
We read every application personally. Complete this form and we will be in touch within 5 business days. Please reply to your confirmation email with your CV attached.
After submitting, you will receive a confirmation email. Please reply to it with your CV attached as a PDF. We keep all applications confidential and do not share your details externally.
We read every application personally. Complete this form and we will be in touch within 5 business days. Please reply to your confirmation email with your CV attached.
After submitting, you will receive a confirmation email. Please reply to it with your CV attached as a PDF. We keep all applications confidential and do not share your details externally.
We read every application personally. Complete this form and we will be in touch within 5 business days. Please reply to your confirmation email with your CV attached.
After submitting, you will receive a confirmation email. Please reply to it with your CV attached as a PDF. We keep all applications confidential and do not share your details externally.
We read every application personally. Complete this form and we will be in touch within 5 business days. Please reply to your confirmation email with your CV attached.
After submitting, you will receive a confirmation email. Please reply to it with your CV attached as a PDF. We keep all applications confidential and do not share your details externally.