Project case study · 2026

Sentinel Geopolitical RAG Platform

A full-stack intelligence system that turns continuously ingested reporting into grounded, source-cited analysis.

Role
AI / Full-Stack Engineer
Year
2026
Technologies
FastAPIReactChromaDBSentenceTransformersRedisPostgreSQLDocker
View project on GitHub

Problem

Analysts need a way to search a changing news corpus while retaining source traceability.

Approach

Sentinel ingests news and research sources asynchronously, normalizes and semantically chunks articles, embeds them, ranks retrieval results, and generates answers that retain citations.

Architecture

scheduled ingestion → enrichment and chunking → ChromaDB + PostgreSQL → retrieval and source ranking → answer generation → React dashboard

Implementation

FastAPI services coordinate ingestion and retrieval, Redis provides caching, PostgreSQL keeps persistent metadata, and a React interface exposes the workflow. Docker packages the system for deployment.

Evidence

The implementation demonstrates the complete flow from scheduled ingestion to retrieval and grounded answers with source citations. This is system-level evidence; it does not imply a numerical accuracy result.

Limitations

Retrieval quality depends on source coverage, chunking, and the quality of upstream publications.