The new rail solution will enable railways to efficiently and systematically map all existing rail assets and introduce new capabilities for digital asset management in a dynamic environment. Jeremy Suard, co-founder and CEO of Exodigo, explains how the solution works and how its performance, scalability, and operational impact differ from its competitors.
Exodigo is an underground intelligence company that helps infrastructure owners, engineers, and contractors reduce cost, schedule, and safety risks on critical infrastructure projects. Its core product is an AI-powered multi-sensor mapping platform that provides accurate design-ready subsurface intelligence in both 2D and 3D formats. Beyond mapping, Exodigo also offers AI-driven engineering services that integrate subsurface intelligence directly into design, project management, and construction workflows.
New underground mapping solution for railways
Exodigo recently announced that it has successfully developed and deployed an advanced underground intelligence system designed specifically for rail infrastructure projects. At the 2026 International Consumer Electronics Show (CES 2026) in Las Vegas, the company introduced its underground mapping solution for railways and its first successful implementation with Israel Railways. The solution is built as an end-to-end subsurface intelligence system that combines remote analytics, field-based sensing, and AI-driven data fusion to provide engineering-ready subsurface insights.
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The process begins with AI-driven desktop mapping. Exodigo collects and analyzes existing records, in-construction images, and historical satellite imagery to establish an initial understanding of subsurface conditions and identify gaps and risk areas. Exodigo then conducts on-site multi-sensor scans, deploying proprietary non-intrusive sensing technologies such as ground-penetrating radar and electromagnetic sensors to collect extremely dense datasets of over 500 GB per acre.
On the software side, Exodigo’s AI platform processes and fuses these inputs, overlaying recordings and remote imagery with high-resolution field sensor data. Advanced machine learning models interpret signals, resolve conflicts between datasets, and confidently classify subsurface utilities and features.
The output is a multidimensional underground model that identifies up to 90% of underground facilities without any hassle. Built according to the American Society of Civil Engineers (ASCE) Subsurface Utility Engineering (SUE) standards, this integrated hardware and software approach transforms fragmented and uncertain subsurface information into a single, actionable source of subsurface truth for design and construction.
New features for digital asset management in dynamic environments
The multidimensional subsurface model produced by Exodigo is more than a static visualization. These serve as a living digital underground layer that can be directly integrated into railway digital asset management and engineering workflows.
By linking verified subsurface intelligence to existing rail assets, operators obtain a continuously accessible baseline that supports planning, maintenance, and development in dynamic operating environments. These models allow teams to assess how underground conditions interact with track systems, signaling, electrification, drainage, and adjacent utilities, improving coordination between disciplines and reducing reliance on outdated records.
Models are generated at the corridor scale and can be updated as new data is collected, enabling proactive maintenance planning, risk-aware design for upgrades and expansions, and rapid response to unexpected situations. In practice, this introduces new digital asset management capabilities that move rail organizations from reactive, assumption-based decision-making to AI-enabled, data-driven management of underground assets across the rail network lifecycle.
Key differentiators and challenges addressed by Exodigo’s new solution
Exodigo has demonstrated clear superiority through its combination of performance, scalability and operational impact during extensive rail line trials. The key differentiators are:
- High-speed data collection: Continuous mapping can be performed from systems installed on railways without track closures or service interruptions.
- Data quality and accuracy: Clear and consistent detection and classification of underground assets over long corridor sections
- Comprehensiveness: Multisensor fusion provides richer and more reliable results than single technology approaches.
- Operational Readiness: Ability to deploy on existing rail vehicles and operate within real-world rail constraints.
In a comparative evaluation against multiple global vendors, Exodigo’s solution stood out as the most mature, scalable, and infrastructure-ready technology.
The results presented by Exodigo demonstrate great potential not only for Israel Railways, but also for railway operators around the world who face common challenges such as aging infrastructure, incomplete or obsolete underground records, increasing capacity demands, and pressure to minimize service interruptions during maintenance and expansion.
Traditional underground investigation methods are time-consuming, destructive, and often have limited coverage, making it difficult to maintain accurate asset inventories and plan projects with confidence. Exodigo’s solutions address these challenges by enabling:
- Subsurface mapping of your entire network without drilling or downtime
- Integrated and continuously updated underground source of truth
- Reduce the risk of asset strikes, delays, and cost overruns
- Smarter long-term planning for maintenance, electrification, signaling and expansion projects
As demonstrated by Israel Railways, this technology is applicable far beyond a single use case, providing rail operators around the world with a scalable way to modernize rail asset management and improve service reliability.
