Solutions Solution · Mobility & Infrastructure

Real-Time Asset Intelligence

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.

Energy FleetIndustrial AssetsTelemetry
−34%
Reduction in fuel usage and unplanned downtime
Predictive
Failures detected before they occur
Real-time
Asset health across every connected device
97%
On-time dispatch reliability post-deployment
The problem

Assets fail reactively. Intelligence should be predictive.

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.

DATA ENGINEERING

Telemetry ingestion at scale

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.

IoT sensor integrationVehicle telemetry (OBD / CAN bus)Azure IoT HubKafka event streaming
Data sources connected
  • Vehicle telemetry — engine health, fuel, location, speed, driver behaviour
  • Equipment sensors, vibration, temperature, pressure, cycle counts
  • Energy meters, consumption, load, fault codes, charging state
  • Environmental feeds, route conditions, weather, traffic impacting asset performance
Operational result
  • Every asset emitting a live signal, no dark fleet or unmonitored equipment
  • Data normalised across different asset types and OEM data formats
  • Historical telemetry stored for pattern analysis and model training
AGENTIC AI

Anomaly detection, prediction and alerting

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.

Predictive maintenance modelsAnomaly detectionRemaining useful life predictionOperational impact scoring
What AI detects and predicts
  • Mechanical degradation, vibration, temperature and pressure deviations before failure
  • Fuel and energy inefficiency patterns indicating route, load or asset issues
  • Battery health deterioration in EV fleets, charge cycle degradation and range impact
  • Driver behaviour patterns correlating with vehicle wear and accident risk
Operational result
  • Failures predicted days or weeks ahead, maintenance scheduled before breakdown
  • Operational impact calculated before a maintenance decision is made
  • AI separates genuine alerts from noise, maintenance teams act on signals that matter
INTELLIGENT AUTOMATION

Automated maintenance and dispatch workflows

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.

Maintenance management system integrationDispatch system workflowsParts inventory automation
What gets automated
  • Work order generation and technician scheduling from predictive alerts
  • Spare parts and inventory reservation triggered ahead of scheduled maintenance
  • Dispatch and route reallocation when an asset is pulled for maintenance
  • Asset availability status propagated across fleet management, dispatch and customer systems
Operational result
  • Maintenance response time reduced from days to hours
  • Spare parts availability aligned with predicted maintenance schedule
  • Operational disruption minimised, maintenance planned, not emergency
PRODUCT ENGINEERING

Asset intelligence platform

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.

Live asset health dashboardPredictive health scoring UIFleet utilisation analyticsMobile field interface
Platform capabilities
  • Live asset map — every asset with real-time location, status and health score
  • Predictive health dashboard, risk-scored assets with projected failure timeline
  • Maintenance planner, upcoming scheduled work aligned with operational demand
  • Utilisation analytics, efficiency, fuel, route and driver performance trends
Operational result
  • Fleet and maintenance managers operate from one source of truth
  • Maintenance decisions made with operational impact visibility
  • Asset utilisation optimised continuously, not reviewed quarterly
PLATFORM OPS & GOVERNANCE

Continuous telemetry reliability and data governance

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.

Telemetry feed monitoringData quality governance99.9% pipeline uptime SLA
What gets governed
  • Telemetry feed completeness, every asset signal gap detected and flagged immediately
  • Data quality validation, values within expected range, anomalies distinguished from sensor faults
  • Pipeline latency monitoring, sub-second data delivery maintained across all feeds
  • Compliance and audit, asset data retained, traceable and accessible for regulatory requirements
Operational result
  • Predictive models trained on clean, complete data, not corrupted by sensor noise
  • Operations teams trust the alerts because the data is governed
  • Regulatory compliance for asset data maintained without manual effort
Industry application

Asset intelligence across sectors.

Fleet & EV Networks

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.

Energy & Industrial Assets

Power generation, pipeline, turbine and industrial equipment monitoring, failure prediction, load optimisation and maintenance scheduling across geographically distributed infrastructure.

Port & Logistics Equipment

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.

Frequently asked questions: Asset Intelligence

What data does asset intelligence use to predict failures?

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.

Which sectors does real-time asset intelligence apply to?

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.

Does Infarsight provide the IoT platform or does it connect to existing infrastructure?

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.

Ready to build predictive asset intelligence?

We start with an asset audit, mapping your current monitoring coverage, telemetry sources and highest-cost unplanned maintenance events.

Book an Asset Audit →
Solutions Solution Category

Operational Control Towers

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.

95%
Faster response TAT with TripSight
34%
Less fuel consumption with FleetSight
2.1s
Avg automated resolution time
TripSight — Travel Operations Control Tower

The unified command center for travel operations.

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.

  • Live flight ops, passenger disruption & crew status dashboard
  • Automated rebooking, 147 passengers resolved in 2.4 seconds
  • Hotel yield with real-time demand signals & competitor rates
  • Ground crew allocation driven by live gate & flight data
  • SLA tracking & financial exposure monitoring in real time
Explore TripSight →
FleetSight — Fleet Operations Control Tower

Intelligence for every vehicle in your fleet.

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.

  • 284+ vehicles tracked live, health, location, ETA adherence
  • Predictive dispatch based on vehicle health telemetry
  • EV charging network state, availability, faults, demand
  • Zero-delay airport transfer coordination with live flight sync
  • Driver routing optimised for real-time traffic & load
Explore FleetSight →
What makes a control tower different from a dashboard?

Dashboards show data

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.

Control towers create 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.

The difference: 34 minutes vs 2 seconds

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.

Ready to build your operational control tower?

We deploy TripSight or FleetSight in weeks, with pre-built connectors for your existing systems.

Request a demo →
Solutions Solution Category

Decision Intelligence 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.

€150K+
Avg cost of one airline decision delay cascade
11 min
Decision window before airline action costs compound
2.1s
DecisionSight resolution time vs 34 min manual
4–6×
Cost: reactive vs proactive decision-making
The decision latency problem

Every Minute Between an Operational Event
and an Action Has a Revenue Cost.

In complex operations, airlines, ports, fleets, logistics, the decision window is always shorter than the decision process. Until now.

The cascade that kills margin

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.

Why existing tools fail

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.

The solution isn't faster reporting

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: the digital twin approach

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.

How Decision Intelligence works
01

Operational state modelling

  • Live digital twin of your entire operation
  • Continuously updated from ERP, IoT, CRM, APIs
  • Entity relationships and dependency graph
  • Historical pattern learning
→ Always-current operational context
02

Event & anomaly detection

  • Real-time threshold monitoring
  • Pattern deviation detection
  • Cross-system risk correlation
  • Pre-emptive impact assessment
→ Signals before they become incidents
03

Decision reasoning

  • LLM-powered reasoning across full context
  • Policy & constraint encoding
  • Multi-option scenario simulation
  • Financial impact quantification
→ Optimal action selected automatically
04

Automated execution

  • Direct system actions, booking, dispatch, alert
  • Multi-system coordination in parallel
  • Human escalation for high-stakes decisions
  • Confidence-based routing
→ Decision executed in milliseconds
05

Audit & learning

  • Full audit trail for every decision
  • Outcome tracking against prediction
  • Model retraining from feedback
  • Explainability for governance
→ System improves continuously
ACCELERATOR

DecisionSight

Our proprietary Decision Intelligence platform, digital twin, scenario simulation and automated decision execution for Travel and Mobility operations.

Explore DecisionSight →

Ready to eliminate decision latency?

We begin with a decision latency audit, mapping your most costly operational decision delays and sizing the automation opportunity.

Book a decision mapping session →