According to the UN-HABITAT, the city of Nairobi loses half a million USD daily due to congestion on roads designed for a city 10 times smaller. Therefore, there is a great need for traffic management and awareness solutions. Many existing solutions are unsuitable for cities like Nairobi due to economic constraints, dynamic events, uncertainty, and poor infrastructure. Recently, a novel approach called Frugal Innovation has been adopted at IBM Tokyo Research. The approach combines very low quality images (VLQI) captured by existing low-cost cameras with network flow algorithms to accurately estimate traffic flow. We extend their work to develop a mobile app, called Twende-Twende, that provides drivers with real-time traffic information and suggested routes. We incorporate locally relevant context (such as references to landmarks) to predict congestion and create traffic awareness. We deployed the app and evaluated its effectiveness, accuracy and usability. Our initial evaluation indicates that the app enhances the driving experience and can be deployed in other developing countries.