RAILwAI

What RAILwAI does

RAILwAI is a French B2B software company, founded in 2021 and headquartered in Montpellier, that sells an AI-powered modular platform for predictive maintenance of railway and guided-transport infrastructure. The platform addresses a documented fragmentation problem — the company states that approximately 87% of collected rail data goes unused — by centralizing inputs from GMAO (Computerized Maintenance Management) systems, embedded track and catenary sensors, inspection wagons, weather stations, and digital maintenance forms into a single operational environment. Its product suite is built around a foundational Data Station module that ingests and formats data, plus six specialized analytical modules — MIDA (intelligent condition-based maintenance), Geometry (linear defect management), Weather (climate hazard surveillance and automated work-order generation), Traffic (circulation non-conformities), Inspection (point-defect detection using image, video, and LiDAR), and Signalling (subsystem defect contextualization) — that apply machine learning and predictive analytics to forecast degradation, detect anomalies, and adapt maintenance cycles to actual equipment stress.

The company serves enterprise customers across the European rail value chain — infrastructure managers, passenger and freight operators (including Transdev, Eurotunnel, RATP, FGC, Metro Málaga, and EUROPORTE), engineering and construction firms, and sensor manufacturers. RAILwAI operates a direct enterprise sales motion with quote-based SaaS subscriptions billed annually, and pricing is not publicly disclosed. A 17-person team is organized into four competence poles (Strategy & Operations, Technical, R&D & Innovation, and Commercial), and the company has assembled a deep partnership ecosystem spanning GMAO vendors (Carl, IBM Maximo, Altair Enterprise, SAP, Mainta), sensor and inspection providers (ERTMS Solutions, Sencrop, INEO, VAPERAIL, Konux, Sensonic, MER MEC), French public institutions (Ministère chargé des transports, AIT, BPI France, La French Tech), and academic research bodies (RAILENIUM, Rail Open Lab, LIRMM, CNRS, I-Trans, Cluster TOTEM). It claims quantified outcomes including a 15% reduction in maintenance costs and a 30% reduction in failures and breakdowns, and positions itself as a data-aggregation and interoperability layer rather than a competing sensor or GMAO vendor.

Name

RAILwAI

Legal name

RAILwAI

Website

https://railwai.com

Company type

Private

Founded year

2021

Operating status

Operating

Headcount range

11–50 employees

Short description

RAILwAI is a French B2B SaaS company providing an AI-powered modular platform for predictive maintenance of railway and guided-transport infrastructure. It centralizes fragmented sensor, GMAO, and inspection data into actionable maintenance intelligence for European infrastructure managers, railway operators, and engineering firms.

Ownership category

akta.pro rank

Product category

Rail Infrastructure Predictive Maintenance Software

NAICS

Support Activities for Rail Transportation (4882), Support Activities for Rail Transportation (488210), Urban Transit Systems (4851)

SIC

Transportation Services (4700)

akta.pro primary industry

Rail Asset Inspection, Monitoring & Diagnostics (Track Geometry, Wayside Sensors) (TLAJADAG)

akta.pro secondary industries

Track Infrastructure Management & Maintenance (Rails, Sleepers, Ballast, Turnouts) (TLAJADAA), Rail Signaling & Train Control Infrastructure (Interlockings, ETCS/CBTC Wayside) (TLAJADAB), Freight Wagon (Railcar) Maintenance & Repair (TLAKAIAB)

Keywords

• Predictive maintenance software
• Rail infrastructure analytics
• Railway asset management
• Transport infrastructure AI
• Condition-based monitoring

Headquarters

HQ city

Montpellier

HQ country

France

HQ region

Europe

Offices1 record

Markets served

GTM type

B2B

Offering type

Software

Cost components

Technology or R&D, Personnel, Marketing or Sales, Infrastructure, Operations

Revenue model

1. Software Platform Subscription: B2B SaaS subscription model providing access to modular predictive maintenance platform with multiple specialized modules. Revenue derived from software licensing with potential for customization and professional services.

Pricing tiers

Go-to-market motion1 record

Distribution channels1 record

Marketing channels4 records

Core offering

RAILwAI provides a modular, AI-powered SaaS platform for predictive maintenance of guided transport (rail) infrastructure. The platform centralizes fragmented data from sensors, inspection wagons, GMAO systems, and client information systems, then applies advanced analytics and predictive models to enable condition-based intelligent maintenance, defect detection, and maintenance cycle optimization for infrastructure managers and railway operators.

Product overview

RAILwAI provides a modular, interoperable software platform for railway infrastructure maintenance optimization. The platform consists of a core module called Data Station (which serves as the data collection and formatting foundation) plus six specialized analytical modules: MIDA (intelligent conditional maintenance), Weather (climate monitoring), Traffic (circulation management), Geometry (linear defect analysis), Inspection (point defect detection), and Signalling (signal system management). These modules work together to centralize data from diverse sources (sensors, inspection wagons, information systems, GMAO), apply AI for analysis and prediction, and generate maintenance forecasts and recommendations, enabling infrastructure managers to transition from preventive to intelligent conditional maintenance.

Differentiator

Problem solved

Functional benefit

Brands

• MIDA: Module for optimizing maintenance interventions, surveillance and renewal of railway infrastructure by adapting maintenance cycles to actual equipment stress.
• Data Station
• Geometry
• Weather
• Traffic
• Inspection
• Signalling

Products and services

• Data Station Foundational module of the RAILwAI platform that interfaces with client systems via API to collect and format data from sensors, inspection wagons, information systems, and GMAO systems. Provides a centralized view of railway infrastructure data with segmentation by criteria and indicators, with no data visualization expertise required. Targets rail infrastructure managers and railway operators.
• Geometry Linear defect management and enrichment module for processing data from embedded sensors. Consolidates track geometry, catenary, LAC, wear, ballast, and gauge defects into a single interface with automatic defect classification and threshold crossing projections. For rail infrastructure maintenance teams.
• Weather Weather monitoring automation module that calculates rail or catenary temperature from air temperature, reduces unnecessary field surveillance, and integrates with GMAO to automatically generate work orders. Includes 14-day weather forecasting support for maintenance planning. For rail infrastructure managers and maintenance operators.
• Traffic Railway circulation non-conformity management module that centralizes rolling stock non-conformities, identifies infrastructure anomalies related to wheel quality, evaluates wagon weight balance, and calculates actual tonnage circulated. For railway operators and infrastructure managers.
• Inspection Point defect detection and tracking module that uses data from recording wagons, image capture systems, and LiDAR with spatial and multivariate analysis. Identifies localized anomalies on rails, sleepers, switches, bridges, and tunnels. For rail infrastructure maintenance and inspection teams.
• Signalling Railway signalling subsystem defect management and contextualization module. Tracks individual equipment status, detects potential problems, and facilitates experience feedback (REX) for maintenance optimization to ensure safety of passengers, drivers, and railway staff. For rail signalling maintenance teams.
• MIDA Intelligent condition-based maintenance module that optimizes maintenance, surveillance, and renewal interventions by adapting maintenance cycles to actual equipment stresses and operational planning constraints. Integrates with existing GMAO systems for dynamic, individualized maintenance. For infrastructure managers.

Quantifiable outcome

• 15% reduction in maintenance and upkeep costs
• +3 more outcomes

Named customers10 records

Segments5 records

Ideal customer profiles4 records

Technology focussed Yes

API detail

Has API

Yes

API docs

API detail

Core technology

AI maturity

App detail

Integration14 records

AI capability8 records

Feature7 records

Partnerships

23 partnerships are on record, tiered core and minor.

• ERTMS SolutionscoreTechnology or IntegrationSensor technology and monitoring system integration partner for railway applications, providing data for the RAILwAI predictive maintenance platform
• SencropcoreTechnology or IntegrationWeather sensor integration partner contributing to the Weather module for climate hazard surveillance
• INEOcoreTechnology or IntegrationRailway sensor technology partner integrated with the RAILwAI platform for infrastructure monitoring
• VAPERAILcoreTechnology or IntegrationRail inspection and monitoring technology partner providing data for defect detection and analysis
• KonuxcoreTechnology or IntegrationAI-based rail infrastructure monitoring technology partner featured on the references page
• SensoniccoreTechnology or IntegrationSensor technology partner for railway monitoring and infrastructure analysis
• MER MECcoreTechnology or IntegrationRailway inspection systems manufacturer partner providing integrated data sources
• Carl SoftwarecoreTechnology or IntegrationGMAO (Computer-Aided Maintenance Management) system integration with data import capabilities
• IBM MaximocoreTechnology or IntegrationEnterprise asset management GMAO system integration for data exchange
• Altair EnterprisecoreTechnology or IntegrationEnterprise GMAO platform integration for maintenance data management
• SAPcoreTechnology or IntegrationEnterprise ERP GMAO integration for comprehensive data connectivity
• MaintacoreTechnology or IntegrationGMAO system integration for maintenance management data import
• ERMEOcoreTechnology or IntegrationMaintenance form integration partner for specific maintenance forms integrated into the RAILwAI platform
• La French TechcoreOthersFrench technology ecosystem partner supporting innovative startups in France
• Google for StartupsminorOthersTechnology ecosystem partner providing cloud infrastructure and startup resources
• RAILENIUMcoreStrategic or Co-development PartnerFrench rail research institute and innovation cluster partner for rail technology development
• Rail Open LabcoreStrategic or Co-development PartnerRail innovation laboratory partnership for collaborative R&D in rail technology
• LIRMMcoreStrategic or Co-development PartnerMontpellier Computer Science, Microelectronics and Robotics Laboratory - academic research partnership
• CNRScoreStrategic or Co-development PartnerFrench National Centre for Scientific Research academic partnership for advanced research
• I-TranscoreStrategic or Co-development PartnerFrench rail and public transport innovation cluster for collaborative projects
• Ministère chargé des transportscoreStrategic or Co-development PartnerFrench Ministry of Transport as institutional partner and client
• Agence de l'innovation pour les transports (AIT)coreStrategic or Co-development PartnerFrench transport innovation agency partnership for innovation in transport sector
• Cluster TOTEMcoreStrategic or Co-development PartnerRail and mobility technology cluster partnership in the Montpellier region

Scale indicators9 records

Recent moves6 records

Expansion highlights6 records

Direct peers

• Konux: Konux is a Munich-based AI software company that applies machine learning to railway switch and infrastructure monitoring, enabling predictive maintenance. It is the closest direct competitor to RAILwAI in AI-driven rail infrastructure analytics and is also listed as a partner on RAILwAI's site.
• Bentley Systems: Bentley Systems offers AssetWise and OpenRail for managing linear rail infrastructure assets, including inspection data, condition monitoring, and lifecycle analytics. It competes with RAILwAI in the rail infrastructure asset management software layer that infrastructure managers use to plan maintenance.
• Trimble: Trimble provides rail asset monitoring, mapping, and condition-assessment solutions used by infrastructure managers to prioritize maintenance. Its rail portfolio overlaps with RAILwAI's inspection and geometry workflows for diagnosing track and structure conditions.
• MER MEC: MER MEC manufactures diagnostic and inspection systems (track geometry cars, catenary monitoring) and supplies data that infrastructure managers feed into maintenance planning. RAILwAI lists it as a sensor/inspection partner, and its measurement data sits in the same value chain that RAILwAI's platform analyzes.

Emerging players

• Sensonic: Sensonic provides fiber-optic sensing solutions for continuous rail infrastructure monitoring, including intrusion detection and asset health. It is also a RAILwAI partner, and together they sit in the overlapping space of distributed sensing and analytics for rail asset health.

Broad incumbents

• Siemens Mobility: Siemens Mobility is a major rail OEM and digital solutions provider with rail infrastructure monitoring offerings (e.g., Railigent, MindSphere rail applications). Its installed base and rail-specific digital portfolio position it as a broad incumbent alternative to RAILwAI's modular analytics platform.
• Alstom: Alstom is a global rail OEM that has built digital services around signaling, infrastructure monitoring, and predictive maintenance (e.g., HealthHub, augmented fleet management). It serves many of the same European rail customers as RAILwAI and represents an incumbent competitive threat.
• Hitachi Rail: Hitachi Rail delivers digital asset management, condition monitoring, and predictive maintenance solutions for signaling, rolling stock, and infrastructure worldwide. Its broader portfolio overlaps with RAILwAI's infrastructure analytics, making it a wide-incumbent competitor in the same accounts.
• Wabtec: Wabtec (which absorbed GE Transportation) provides rail equipment, digital solutions, and asset performance management for transit and freight operators globally. Its TriMetrix/GoLinq-style platforms compete with RAILwAI at the predictive maintenance and asset analytics layer for infrastructure managers.

Others

• IBM (Maximo Application Suite): IBM Maximo Application Suite is an enterprise asset management platform that RAILwAI explicitly integrates with; it can also serve as an adjacent competitor for predictive maintenance use cases at rail infrastructure operators. Included as an ecosystem participant that is both partner and potential substitute.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat6 records

Key risks6 records

Key highlights7 records

Customer concentration

• LinkedInlinkedin.com/company/railwai

Compliance1 record

Revenue estimate

Valuation estimate

Number of profiles

Profiles7 records

Funding overview

Funding rounds

Investors

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about RAILwAI