Indian Railways runs 1.32 lakh kilometers of track. It moves over 13 million passengers every day. And it still relies heavily on manual inspection to keep that network safe.
That gap between scale and method is exactly what a new private sector partnership wants to close.
Nova Control Technologix, a subsidiary of Bengaluru-based e2E Rail, has signed a partnership with Tata Elxsi to integrate artificial intelligence into railway signaling systems, train coaches and other critical railway equipment. The objective is to build predictive systems that identify potential failures and safety risks before they occur. Nova Control plans to invest Rs 100 crore over the next two to three years to develop this technology stack.
From Reactive To Predictive
The fundamental problem the partnership targets is one Indian Railways has lived with for decades. Railway maintenance has been reactive. A component fails, crews respond. A track defect appears, inspectors flag it. The system fixes problems after they surface.
Sourajit Mukherjee, Director and CEO of Nova Control Technologix and CEO of e2E Rail, framed the shift clearly. “Historically, railways have largely been reactive when it comes to maintenance. As railway systems evolve and there is a need for faster, safer and more efficient operations, we are entering an era where systems must continuously monitor themselves and predict failures before they happen. That is the fundamental idea behind integrating AI into railway infrastructure,” he said.
Tata Elxsi brings cybersecurity and data protection expertise to the partnership. Its role is to build secure rail safety networks around the AI systems Nova Control develops. Railway signaling infrastructure is critical national infrastructure. An unsecured AI layer on top of it creates new attack surfaces. Tata Elxsi’s involvement addresses that risk from the design stage.
Digital Twins Before Deployment
One of the more technically significant elements of the partnership is the use of digital twin technology. The companies plan to simulate and validate AI models inside a digital replica of railway infrastructure before deploying anything on Indian Railways’ actual network.
Jayaraj Rajapandian, Head of Aerospace, Rail and Off-Highway at Tata Elxsi, explained the design philosophy. “From the very beginning, while architecting the product, we ensured that an AI engine was an integral part of the design. We deliberately built an architecture that is modular, scalable and expandable, while also allowing flexibility to scale down wherever required. From both safety and predictive maintenance perspectives, the architecture allows us to deploy advanced algorithms that support decision-making and ensure safer and more efficient railway operations,” he said.
Mukherjee added that the combination of AI analytics and digital twins detects anomalies early, predicts asset degradation, reduces downtime and directly improves punctuality and operational efficiency.
“Higher asset availability makes railway operations more reliable and ultimately enhances the passenger experience,” Mukherjee said.
The Numbers Behind The Urgency
Industry estimates place Indian Railways’ annual spend on safety and maintenance at approximately Rs 1 lakh crore. Of that, 65 to 70 percent goes toward maintaining existing assets. Experts believe wider adoption of AI-driven predictive maintenance could bring that figure below 50 percent.
That is not a marginal saving. On a Rs 1 lakh crore base, halving the maintenance cost share frees up tens of thousands of crores annually for capacity expansion, new rolling stock and passenger experience upgrades.
“Indian Railways deploys a massive workforce for maintenance because of the sheer scale of its operations. AI has the potential to fundamentally change this by making systems self-diagnostic, self-predictive and eventually more autonomous. By leveraging AI and ML, these systems can identify patterns, predict failures before they occur and recommend corrective action,” Mukherjee said.
What Government Is Already Doing
The Nova Control-Tata Elxsi partnership arrives inside a broader government push. Indian Railways has already deployed the Machine Vision Inspection System at six locations to detect loose or missing train components in real time. It has installed 24 Wheel Impact Load Detector systems and 25 Online Monitoring of Rolling Stock systems to monitor bearing and wheel health across the network. The Research Designs and Standards Organization is developing TRI-Netra, a fog vision system combining optical cameras, infrared sensors and LiDAR to assist loco pilots in poor weather.
The Rail Tech Policy, approved in February 2026, provides 50:50 cost-sharing between Indian Railways and private innovators for prototype development and trials, actively incentivising exactly the kind of partnership Nova Control and Tata Elxsi have formed.
The private and public sectors are now moving in the same direction. The question is speed. Indian Railways’ 1.32 lakh-km network is vast. Deploying AI at meaningful scale across it will take years and sustained investment. But the direction is set. The era of railways that fix problems after they happen is ending. The era of railways that see them coming is beginning.
