Track Safety AI

AI-driven geospatial mapping detects structural faults and track anomalies in real time, enabling proactive maintenance and reducing derailment risks network-wide.

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How does it work?

Manual inspections of tracks and bridges are time-consuming and may miss early-stage defects, risking service disruptions and safety hazards. AI-based geospatial analytics provides continuous, high-resolution monitoring to identify structural anomalies before they escalate, enhancing maintenance efficiency and infrastructure safety.

Continuous Monitoring: Automated analysis of satellite and drone imagery delivers constant oversight of tracks and bridges. This continuous monitoring uncovers deviations in geometry and surface conditions without manual intervention.
Early Fault Detection: AI models identify subtle cracks, deformations, and vegetation encroachment before they worsen. Early alerts enable timely repairs, minimizing the risk of derailments and service interruptions.
Risk Reduction: Quantitative risk scores prioritize sections with the highest defect probability. Maintenance teams focus resources efficiently, reducing inspection backlog and enhancing passenger safety.
Optimized Maintenance: Predictive insights guide maintenance schedules based on actual asset condition rather than fixed intervals. This approach cuts unnecessary inspections and lowers repair costs by up to 20%.
Detailed Analytics: High-resolution 3D maps and thermal data reveal structural weaknesses hidden from traditional surveys. Interactive dashboards provide engineering teams with actionable metrics on wear patterns and load stresses.
Scalable Coverage: Cloud-based processing supports analysis of thousands of kilometers of rail corridors and hundreds of bridges. The platform integrates with existing GIS systems to extend monitoring across entire networks.

Frequently asked questions

Have a different question and can’t find the answer you’re looking for? Reach out to our support team by sending us an email and we’ll get back to you as soon as we can.

How does this compare to manual inspections?: AI-based geospatial monitoring provides higher frequency and objectivity than manual inspections, reducing human error. It complements on-site checks by highlighting areas requiring immediate attention, not replacing physical assessments entirely.
What makes this solution more popular than traditional sensors?: Geospatial analytics covers large areas cost-effectively without installing hardware on every structure. Its popularity stems from comprehensive coverage and rapid deployment compared to fixed sensors.
Are there limitations when using satellite imagery?: Satellite data can be affected by clouds and revisit intervals, potentially delaying detections. Combining drone or aerial imagery mitigates these limitations for critical segments requiring higher temporal resolution.
Can I use this platform with alternative data sources?: Yes, the platform supports integration of LiDAR, thermal cameras, and IoT sensor feeds alongside optical imagery. This flexibility enhances anomaly detection by leveraging multiple data modalities.
How accurate are the AI-driven defect detections?: Our models achieve over 90% detection accuracy in pilot studies, validated against ground truth inspections. Accuracy varies with image resolution and data quality, but continuous learning improves performance over time.
What are alternatives to geospatial analytics for rail safety?: Alternatives include trackside sensors, manual patrols, and fixed-point inspections, each with higher operational costs or limited coverage. Geospatial analytics stands out by delivering network-wide insights with minimal infrastructure changes.

Geospatial AI Platform

Intelligence

AI & foundation models

Deep-learning and foundation models turn raw imagery into ready-to-use insights, so you ship answers instead of training pipelines.

Experience

Conversational workflow

Ask questions in plain language and the platform responds with charts, visualizations, and next step suggestions.

Speed

GPU-accelerated cloud

Cloud-native architecture spins up on-demand GPU clusters that scale from a single scene to global archives—no manual ops, no bottlenecks.

Data

Any sensor, any format

Optical, SAR, drone, IoT, vector or raster—ingest, fuse, and analyze without conversion headaches.

Visualization

Insight you can see

Real-time 2D / 3D maps and export-ready plots make results clear for engineers, execs, and clients alike.

Boost your productivity. Experience Geospatial AI.

Turn satellite, drone, and sensor data into clear, real-time insights using powerful AI – no complex setup, just answers you can see and act on.

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