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Rail Vision Ltd. reports developments in railway safety technology built around AI-integrated sensing systems for locomotives and rail yards. The company develops multi-spectral electro-optic platforms that provide extended-range situational awareness and real-time obstacle detection, with products including MainLine and ShuntingYard.
Recurring updates cover financial results, commercialization activity with rail operators, installations and demonstrations in markets such as Israel and India, Nasdaq and Frankfurt trading status, and capital-position disclosures. Company news also includes developments at majority-owned Quantum Transportation, which is connected to rail-related quantum error correction technology and quantum-AI research for transportation.
Rail Vision (RVSN) will present its newly launched YardFlow™ solution alongside TrackScout™ and YardFlow Flex™ at InnoTrans 2026 in Berlin from September 22–25, 2026.
YardFlow is designed for industrial and freight railyards, using high-sensitivity electro‑optical sensors and proprietary deep‑learning algorithms to detect on‑track or near‑track hazards up to 200 meters (650 ft) away and issue real‑time alerts to support continuous switching operations. Its compact, modular structure is intended to simplify installation on switching locomotives and railcar movers, while integrated video recording and analytics provide operational insights. TrackScout targets mainline rail operations with long‑range hazard detection, and YardFlow Flex is a multi‑spectral railyard solution tailored for harsh weather and low‑visibility conditions. All systems feature AI‑powered perception and will be showcased at Berlin Messe, Hall 27, Stand 760.
Rail Vision (RVSN) launched YardFlow™, an AI-integrated perception solution for industrial and freight railyard operations, designed to meet varied operational requirements across diverse yard environments.
YardFlow uses high-sensitivity electro-optical vision sensors and proprietary deep-learning algorithms to detect on-track or near-track hazards at distances of up to 200 meters (650 ft) and provide real-time alerts to support continuous switching operations. The compact, modular system can be installed on switching locomotives and railcar movers and includes built-in video recording and analytics for operational insights. YardFlow Flex™ (formerly ShuntingYard) remains available as a multi-spectral option for harsh weather and low-visibility use cases, and the company believes YardFlow will support its expanding commercial collaboration with Railserve.
Rail Vision (RVSN) has rebranded its existing railway safety products, renaming MainLine as TrackScout and ShuntingYard as YardFlow Flex.
TrackScout is a long-range AI perception system for mainline freight and passenger rail networks. It uses multi-spectral electro-optical sensors and deep learning to detect and classify hazards in real time at distances of up to 2,000 meters (1.2 miles), including anomaly and switch-state detection, and provides visual and acoustic alerts. Its modular design is intended to support fast retrofit across diverse locomotive fleets.
YardFlow Flex targets freight and industrial yards, detecting on-track and near-track hazards at up to 200 meters (650 feet) and supporting switch-state, anomaly, and sideswipe detection for rolling stock past the foul line. Both solutions integrate with Rail Vision’s operational intelligence platform, which applies big data analytics, real-time tracking, and continuous event recording.
Rail Vision (RVSN) has been selected for MxV Rail’s locomotive sensor pre-integration testing program under the TCCO Technology Roadmap Program, introducing its AI-powered perception technology to Class I railroads in North America.
The testing supports development of Restricted Speed Enforcement (RSE) capabilities, seen as a key step toward increased rail automation and safety. This phase moves Rail Vision from roadmap participation to active real-world evaluation of its sensor performance. The program is expected to give the company exposure to primary decision-makers at major U.S. freight railroads and a role in shaping future performance standards for RSE-related technologies.
Rail Vision (Nasdaq: RVSN, FSE: C80) reported first half 2026 revenues of $1,015,000, up 328% from $237,000 in first half 2025, driven mainly by ShuntingYard systems delivered to Railserve and services for existing customers. Gross profit rose to $317,000 from $48,000.
The company advanced commercialization by integrating its ShuntingYard technology into Railserve’s YardGUARD system in the U.S., completing field testing with Israel Railways, and finishing a MainLine proof-of-concept with a major Indian rail operator. Rail Vision also acquired a 51% controlling interest in Quantum Transportation to expand long-term AI and quantum error-correction capabilities.
Despite higher revenues, operating loss widened to $8,029,000 and GAAP net loss to $7,310,000. As of June 30, 2026, cash, cash equivalents and restricted cash totaled about $15.6 million, total equity was $15.8 million, and the company had no financial debt.
Rail Vision (Nasdaq:RVSN) reported successful completion of ShuntingYard field testing with Israel Railways, following earlier MainLine deployments. Locomotive drivers and staff evaluated the system in daily shunting operations and reported high satisfaction.
The company is discussing potential ShuntingYard commercialization with Israel Railways and signed a non-binding MOU to integrate its technology into Railserve’s commercially launched YardGUARD/WatchGUARD safety solutions.
Rail Vision (Nasdaq:RVSN) announced its AI-powered ShuntingYard perception system is now integrated into YardGUARD, Railserve’s industrial railyard safety system, recently introduced for commercial deployment.
The technology underpins WatchGUARD, providing real-time situational awareness, obstacle detection, in-cab alerts, and automatic braking, and is being showcased at Railway Interchange 2026 in Omaha.
Rail Vision (Nasdaq:RVSN) signed a non-binding MOU with Railserve, a North American industrial railyard services company, to explore expanding their existing collaboration.
The companies plan to discuss additional ShuntingYard deployments, new use cases, rail car mover applications, and broader rail yard solutions. Any expansion requires a future binding agreement.
Rail Vision (Nasdaq:RVSN) announced that majority-owned subsidiary Quantum Transportation integrated Google Quantum AI’s public experimental surface-code dataset into its Quantum Error Correction (QECC) transformer pipeline.
The team built a standardized data adapter, dynamic attention masking, and an end-to-end training loop for mixed real experimental shots, reducing technical risk and enabling scalable training and benchmarking on an external testbed.
Quantum Transportation’s transformer-based neural decoder IP, licensed from Ramot at Tel Aviv University, is cloud-deployed on AWS and has outperformed classical QEC algorithms in simulations.
Rail Vision (Nasdaq: RVSN) reported full-year 2025 revenue of $1,487,000 (up 14.4% YoY) and year-end cash of approximately $20 million with zero financial debt.
GAAP net loss narrowed to $11.1 million for 2025 from $30.7 million in 2024. Second-half revenue rose to $1.25 million (+132% YoY). The company completed a 51% acquisition of Quantum Transportation and secured regional commercial orders and pilots across Israel, Latin America, Central America and India.