AI-powered smart traffic signal platform for city-scale congestion and emissions management
NoTraffic operates an AI-driven mobility platform that replaces manual traffic signal control with real-time, autonomous intersection management. The tech stack (Python, Django, PostgreSQL, ClickHouse, AWS, Kubernetes) supports video analytics and V2X integration at scale. Engineering dominates the hiring mix with focus on perception, IoT device reliability, and internal NOC tooling — reflecting the operational complexity of deploying hardware and software across multiple city deployments.
Notable leadership hires: Perception Team Lead
NoTraffic builds a cloud-based platform that converts traffic signals into intelligent infrastructure capable of real-time decision-making across entire city grids. The system detects and prioritizes all road users (pedestrians, bikes, cars, buses, emergency vehicles) and applies city-defined policies autonomously — reducing congestion, emissions, and accidents. Cities access a cloud dashboard to configure policies such as transit priority or safety corridors; the AI implements these directives live at each intersection. The platform natively supports V2X (vehicle-to-infrastructure) communication for current and future mobility applications. Founded in 2017, the company operates from Kansas with cross-border engineering presence in Israel.
Backend: Python, Django, PostgreSQL, ClickHouse on AWS. Frontend: React, Angular. Infrastructure: Kubernetes, Terraform, Prometheus, Grafana. Video analytics and V2X integration are core to real-time traffic signal control.
Reducing incident resolution time and improving system reliability across deployed intersections. Active projects focus on automation of monitoring, NOC tool development, and installation validation to reduce partner proficiency gaps.
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.