AI traffic-signal platform turning intersections into connected smart infrastructure
NoTraffic sells an AI and V2X platform that upgrades traffic signals to detect road users and manage intersections in real time. Its stack spans embedded code (C++, Rust, MicroPython, LTE) and cloud analytics (Go, ClickHouse, AWS), while the replacement of Salesforce alongside HubSpot and NetSuite points to a reworked go-to-market stack. Accelerating, sales-heavy hiring plus security roles focused on edge fleet hardening and SOC 2 suggest a push from pilots to scaled city deployments.
NoTraffic, founded in 2017 and headquartered in Overland Park, Kansas, builds a mobility platform for cities and transportation agencies. Sensor units installed at traffic signals detect and classify vehicles, buses, bikes, pedestrians and emergency vehicles, and AI software runs each intersection based on real demand. Agencies set policies such as transit priority or pedestrian safety through a cloud dashboard, and the platform integrates V2X capabilities for connected vehicles. The privately held company has 201–500 employees and hires in the United States and Israel.
NoTraffic uses Python, C++, Go, Rust and MicroPython, with React, Angular and Django, PostgreSQL and ClickHouse on AWS and Azure, plus GitLab, Jenkins and Jira. Business tools include NetSuite, HubSpot and ServiceNow.
Yes. Sales leads NoTraffic's accelerating hiring, followed by marketing and security, with most openings at senior level in the United States and Israel.
Current work includes optimization system deployments, traffic microsimulations, controller communication modules, advanced road-user detection sensors, edge fleet hardening and a penetration testing program.
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NoTraffic's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.