wtf is find-the-perfect-blinkit-location?

Find the Perfect Blinkit Location is a small web project that tries to answer a single question: if a company wanted to open a new Blinkit store or delivery hub in a city, which area would be the best choice. Blinkit is an Indian quick-commerce service that promises very fast grocery delivery, so the location of each small warehouse matters a lot for how quickly orders can reach customers. The author has put the working website on Vercel and links to it from the README. The project uses a map-based view of an area and overlays business factors on top of it. The README lists the things it takes into account: customer demand, population density, nearby residential zones, road accessibility, competitor presence, delivery coverage, and delivery time. Users can look at the map, see the highlighted zones, and get a sense of where a new store would probably do well. One of the screenshots in the repo shows a top predicted zone, which is the area the project flags as the strongest candidate. The stack is kept simple. According to the README it is built with HTML, CSS, and JavaScript, plus a map integration and some data visualization. There is no mention of a backend, a database, or any machine learning model, so the analysis appears to be done client-side using preset factors rather than live data. The author is Ronit Raj, and the README frames this as a demonstration project rather than a production tool. It is meant to show how location intelligence and map visualization can support decisions about where to place a quick-commerce store. The repo has 7 stars at the time of this snapshot.