Top Machine Learning Startups in Rail Industry [2026]

Executive Summary: Which are the Top Machine Learning Startups in Rail Industry?

1. Rail Labs (India) – Deploys IIoT sensors and sliding-flag algorithms to predict wheel shelling, send real-time failure alerts, and extend wheel life.
2. Startrit Infratech (India) – Fuses onboard sensors, satellite imagery, and ML to inspect tracks digitally, spot defects early, and schedule data-driven maintenance.
3. IndustrialCortex (Poland) – Uses computer vision to read wagon codes from video streams, automating freight identification and boosting logistics accuracy.
4. Predact Intelligence (India) – Streams vibration data to an ML engine that forecasts failure points in real time, replacing manual inspection cycles.
5. The Quantum Data Center Corporation (US) – Applies physics-inspired algorithms for rapid crew, equipment, and passenger reallocation during disruptions, slashing recovery costs.
6. Sharkey Predictim Globe (France) – Analyzes historical & live sensor data with ML to flag anomalies, cut downtime, and optimize maintenance spend.
7. FOSINA (France) – Delivers distributed fiber-optic sensing that tracks trains, measures speed, and detects intrusions for real-time traffic management.
8. EYYA (UK) – Installs IoT sensors in railcars and applies AI to schedule proactive cleaning, assuring hygiene and enhancing passenger experience.
9. Pennsy Digital (US) – Offers rugged wireless sensors and ML analytics to predict infrastructure issues like bridge strikes and blocked culverts.

Global Startup Heat Map highlights Emerging Machine Learning Startups in Rail Industry

Through the Big Data & Artificial Intelligence (AI)-powered StartUs Insights Discovery Platform, covering over 7M+ startups, 20K+ technology trends plus 150M+ patents, news articles & market reports, we identified the top machine learning in rail startups.

The Global Startup Heat Map below highlights emerging startups advancing machine learning in rail in 2026, as well as the geo-distribution of 300+ startups & scaleups we analyzed for this research.

According to our data, we observe high startup activity in India and the UK, followed by the US. The top 5 Startup Hubs for machine learning solutions in rail are Bangalore, London, Mumbai, New York City, and New Delhi.

Discover Emerging Machine Learning Startups in Rail [2026]

We hand-picked startups to showcase in this report by filtering for their technology, founding year, location, funding, and other metrics. These emerging startups are advancing machine learning in rail. They work on solutions ranging from predictive maintenance and real-time disruption management to AI-powered train inspections and automated wagon identification.

1. Rail Labs

• Founding Year: 2024
• Location: Bengaluru, India
• Use For: Wheel Shelling Prediction System

Indian startup Rail Labs provides an IIoT-based wheel shelling prediction system for the rail industry. It collects high-speed sensor data from trains, transmits it over communication links, and processes it in a centralized shelling analytical tool. Then, it applies sliding flag detection algorithms and computes a daily sliding index.

Moreover, this solution provides real-time failure alerts, customizable dashboards, and predictive maintenance analytics to extend wheel lifespan. This enhances safety and improves operational efficiency.

Rail Labs prevents shelling-related failures, optimizes maintenance schedules, and reduces lifecycle costs to safeguard rail travel and deliver actionable insights.

2. Startrit Infratech

• Founding Year: 2024
• Location: Chennai, India
• Use For: Digital Track Inspection System

Indian startup Startrit Infratech provides a machine learning-based digital track inspection system. It integrates onboard sensor data, satellite imaging insights, and quantum computing solutions to assess rail conditions in real time and detect anomalies with high precision.

Moreover, the solution utilizes predictive analytics to extract defect patterns and schedule maintenance based on actual asset status. As a result, operators reduce manual survey cycles, decrease unplanned downtime, and enhance network safety.

3. IndustrialCortex

• Founding Year: 2023
• Location: Warsaw, Poland
• Use For: Wagon Code Recognition
• Prominent Partnerships: Industrial Cortex, Live Comply, Google, Microsoft

IndustrialCortex, based in Poland, provides an AI-powered platform to identify rail vehicle numbers from images and live streams in real time. It processes live video feeds and static images through a machine learning pipeline.

This isolates character regions and applies convolutional neural networks to decode wagon identifiers across multiple regional standards. As a result, it provides high accuracy and accelerates freight tracking by fully automating identification tasks.

4. Predact Intelligence

• Founding Year: 2023
• Location: Chennai, India
• Use For: Continuous Condition Monitoring and Failure Forecasting Platform

Indian startup Predact Intelligence provides a continuous condition monitoring and failure forecasting platform. It installs compact sensors on rail carriages to stream vibration and structural data into a centralized machine-learning system for real-time track analysis.

Also, its predictive algorithms forecast specific failure points and timings, and its continuous data capture replaces monthly inspection cycles with up-to-the-minute insights.

Moreover, the platform issues proactive alerts through dashboards, SMS, and email, thereby aligning with existing maintenance workflows and narrowing overnight work windows.

5. The Quantum Data Center Corporation (QDC)

• Founding Year: 2022
• Location: Palo Alto, US
• Use For: Real-Time Algorithmic Decision Support

US-based startup The Quantum Data Center Corporation (QDC) utilizes real-time algorithmic decision support for disruption management in airline and rail operations. It leverages physics-inspired algorithms to ingest live schedule feeds and disruption events. It also computes optimal equipment, crew, and passenger reassignments within seconds.

Moreover, it offers modules for rolling stock recovery, crew recovery, passenger recovery, and integrated recovery to balance delay, cancellation, compensation, and deadhead costs.

This solution refreshes assignments continuously throughout the day of operations. It also reflects emerging disruptions and reduces manual coordination.

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6. Sharkey Predictim Globe

• Founding Year: 2021
• Location: Villeneuve-d’Ascq, France
• Use For: Railway Predictive Maintenance

French startup Sharkey Predictim Globe predicts equipment failures on railway networks. It analyzes historical and real-time sensor data with sophisticated algorithms. This supports identifying patterns that indicate potential faults.

The startup deploys machine learning models that continuously learn from new data and apply anomaly detection to flag deviations from normal operating conditions. Moreover, this solution minimizes unplanned downtime, optimizes resource allocation, and enhances operational safety.

7. FOSINA

• Founding Year: 2020
• Location: Nanterre, France
• Use For: Fiber Optic Sensing Systems

French startup FOSINA delivers fiber optic sensing systems for digital railways to monitor trains, measure speed and length, and detect foreign objects or animal intrusions.

It uses distributed fiber optic sensors connected to the DxS interrogation unit along trackside telecom fibers to acquire continuous strain, temperature, and acoustic data along the entire line.

Moreover, it compensates for sections without GPS coverage and provides real-time train length data to passenger information systems. The AI-driven DxS platform classifies multiple event types in real time over extended fiber ranges per interrogator.

The startup qualifies its sensors for harsh environments and designs its equipment with a compact footprint for sustainable global deployment.

8. EYYA

• Founding Year: 2020
• Location: London, UK
• Use For: AI-powered Train Inspection Solution

UK-based startup EYYA provides an AI-powered train inspection solution that enhances hygiene transparency across rail networks. The startup integrates IoT-enabled sensors into train facilities to collect real-time data on cleanliness and maintenance status.

Further, it utilizes machine learning algorithms to generate actionable insights in scheduling proactive cleaning operations and identifying hygiene issues. By combining predictive analytics with automated reporting, the system promotes accountability, reduces operational inefficiencies, and ensures consistent cleanliness standards.

9. Pennsy Digital

• Founding Year: 2019
• Location: West Chester, US
• Use For: Smart Wireless Sensor Platform
• Prominent Partnerships: ClearBlade, SahayAI

US-based startup Pennsy Digital delivers a smart wireless sensor platform that captures positional, mechanical, and environmental data. Then it streams data via Bluetooth LE, low-power mesh, and cellular links to interoperable IoT platforms.

The platform applies machine learning models to real-time and historical datasets to predict maintenance needs and detect anomalies such as bridge strikes or blocked culverts.

Moreover, it combines rugged, waterproof enclosures, standards-based interfaces, and ten-year battery life to ensure reliable, low-power operation in harsh rail environments.

Discover All Emerging Rail Startups

The rail startups showcased in this report are only a small sample of all startups we identified through our data-driven startup scouting approach. Download our free Rail Innovation Report for a broad overview of the industry or get in touch for quick & exhaustive research on the latest technologies & emerging solutions that will impact your company in 2026!