RAGBackend2025
Docans
A high-performance RAG ecosystem for document analysis and real-time Q&A. Point it at your docs, ask questions, get grounded answers.
Services
- RAG architecture
- Vector search
- FastAPI backend
- React front-end
Challenge
RAG is easy to demo and hard to make fast at scale. The retrieval pipeline had to stay responsive on large document sets — without falling apart the moment a real corpus was loaded in.
Role
Architected the RAG ecosystem end-to-end. Built the FastAPI backend, tuned a Qdrant-backed vector-search pipeline for large-scale retrieval, and shipped the React interface for real-time Q&A.
