The urban traffic in India is more chaotic than ever. The pandemic saw more people adopting cycling as a recreational as well as a healthier and eco-friendly means of commute. The road infrastructure and driving culture in the country are not “cyclist-friendly”, making cyclists more vulnerable than a pedestrian. With an increasing number of beginner cyclists, there is a higher risk of other vehicles shunting them. Although many rider assistance safety solutions exist, they are mostly in their experimental stages, very far from a commercial release. These systems are often expensive as they are early production prototypes which makes them less accessible to the public. This work tries to propose a simple, efficient, and easy-to-make active safety system for cyclists that will act as a third eye. The system relies on low-cost stereo cameras, edge-computing modules, artificial intelligence, and A-GPS to create an active warning system for cyclists, which can be mounted on the back of the bicycles to get voice-assisted warnings when vehicles are dangerously close to them. The data from a fleet of such systems can be collated through a bundled mobile app so that each route in a city can be rated based on the number of close calls/cyclist related accidents per day which gives a safety score for the route allowing riders to choose the safest route and the best time to ride. This whole ecosystem is envisioned as an open source, easy to setup template that any rider/group of riders can use or adapt to their use case with minimum technical knowledge.