IMMOTIC

Residential and commercial listings in Cameroon are scattered across informal channels word of mouth, single-agency sites, social posts with no shared way to search by criteria or see where a property actually sits. IMMOTIC set out to put listings, search and geography in one place.

The data model is geography-first: every listing carries a PostGIS point, so searching by radius, neighbourhood or map viewport is a database query, not an application-layer filter. Django REST Framework exposes that as a typed API; Next.js and TypeScript consume it for search, listing pages and user accounts. The Google Maps API handles rendering and geocoding on top of coordinates the backend already validated.

Built end to end: the Django/DRF backend and its PostGIS schema, the advanced filter and search engine, authentication and user spaces, the Next.js/Tailwind frontend, and the Google Maps integration for browsing listings spatially.

Also handled the parts that don't show up in a demo collecting and structuring real listing data with the client, tuning the site for performance and SEO, deploying to Vercel, and training the client to use and maintain it.