Rail Vision is an early-stage Israeli technology company that makes AI-powered obstacle detection systems for trains. The core problem Rail Vision addresses is a fundamental safety gap: trains traveling at high speeds require braking distances of 600–800 meters or more, but human drivers often cannot detect obstacles at those distances, particularly at night or in poor weather. Rail Vision's systems use a combination of visible-light and thermal cameras mounted on the locomotive, feeding into an onboard computer that uses machine learning to detect and classify hazards — people, animals, vehicles, track anomalies — at ranges of up to 2,000 meters. Rail Vision has two core products: the MainLine System for passenger and freight trains, and the ShuntingYard System for low-speed rail yard operations. Rail Vision sells directly to rail operators, mining companies with private rail networks, and rail services firms, typically starting with a pilot before progressing to a commercial order and potential fleet-wide rollout. Revenue is lumpy and deal-driven, reflecting the early commercial stage. The long-term model depends on fleet expansion with existing customers and a software layer — the D.A.S.H. cloud platform — that aggregates operational data for analytics, though this is still early-stage. The sales cycle is long, requiring demonstrations, pilots, regulatory certification, and integration work. In early 2026, Rail Vision also acquired a 51% stake in Quantum Transportation, an Israeli quantum computing startup, to explore potential synergies with its railway AI systems, though these applications remain exploratory.