In Kenya, close to 70% of agricultural work happens informally much of it by women, youth, and persons with disabilities. They have the land knowledge, labour, and market relationships. What they do not have is the asset lenders demand: collateral. But these farmers are not starting from zero. They have spent a lifetime building assets the formal system refuses to count: trust, verified local networks, a history of in-kind settlements, savings groups, and a productive farm. Hifadhi 2.0 scores that. We bring together: - Community-verified trust built over a lifetime - Verified local network participation—in-kind settlements and savings groups - Satellite-verified farm activity - Transparent, auditable scoring And we do not hand a farmer a number and walk away. Every score comes with an explanation in their local language, so the farmer understands what drove it and what to do next. What comes next: access through feature phones, and AI voice capabilities in local languages for users who cannot read. For farmers: a route from subsistence to scale. For lenders: a credible way into the informal agricultural economy. For the ecosystem: a trust layer that makes invisible productivity visible.

The Smart Study Recommender System is a Retrieval-Augmented Generation (RAG) tool designed specifically for academic use. Built to solve the "information overload" students face during exam seasons, this system ingests course materials (like lecture notes and past papers) and allows users to ask questions grounded strictly in their study data.

Agri Assistant is a production-style agricultural advisory platform built for location-aware crop guidance and document-grounded farm decision support. The project combines a FastAPI backend, retrieval-augmented generation, structured agronomic analytics, and a React frontend into a single end-to-end system for agricultural Q&A.