Velo.AI

Velo.AI is a Pittsburgh, Pennsylvania-based technology startup founded in 2022 by Clark Haynes (CEO) and Micol Marchetti-Bowick (CTO), both Carnegie Mellon University alumni with backgrounds in autonomous vehicle research. Haynes previously worked at Aurora Innovation and Uber's Advanced Technologies Group (ATG); Marchetti-Bowick brings AI and machine learning expertise from CMU's School of Computer Science.

The company's mission is to apply autonomous vehicle perception technology to cyclist safety, addressing one of urban cycling's most dangerous threats: vehicles approaching from behind outside the rider's field of view. Velo.AI's debut product, Copilot, is an AI-powered rear-facing bike light and camera device approximately the size of a deck of cards, designed to mount under a bicycle seat. Copilot uses computer vision algorithms — the same class of models used in self-driving cars — to continuously analyze the traffic environment behind a cyclist. When the system detects an aggressive, distracted, or dangerously close approaching vehicle, it triggers a 90-decibel audible alert and a bright flashing rear light to warn both the cyclist and the driver.

The device is built around the Raspberry Pi Compute Module 4 and incorporates rear-facing video recording for incident documentation. The system differentiates between standard passing traffic and genuinely threatening vehicle behavior, reducing false alarms while maintaining high-sensitivity detection.

Velo.AI conducted street-level prototype testing starting in October 2022 in Pittsburgh with a cohort of urban commuter and recreational cyclists. The company has raised a total of $3.15 million in funding, including investment from URBAN-X (the BMW and MINI urban mobility accelerator) and a $200,000 grant from the US Department of Transportation's Complete Streets AI program. The DOT grant supports Velo.AI's work on using anonymized ride data to provide real-time infrastructure-level safety insights to municipalities.

The company targets urban cyclists, commuters, and safety-conscious recreational riders. Its technology sits at the intersection of consumer safety devices and autonomous vehicle perception systems.