I kept rebuilding the same RAG pipeline for different projects (chunking -> embeddings -> retrieval -> prompt injection), so I tried to turn it into a reusable backend instead.
Ended up building IntelliChat — an open-source, async FastAPI backend for spinning up RAG systems without wiring everything from scratch.
I structured it like a SaaS platform mainly to explore multi-tenant architecture (per-chatbot vector isolation, API key encryption, etc.). Curious if my design is really impactful for collaborative chatbot development.
Core ideas:
Stacks:
Platforms:
A few things I focused on:
Things that were harder than expected:
Current limitations:
Imperial_Benji developed IntelliChat, an open-source backend for reusable RAG pipelines, focusing on multi-tenant architecture and vector isolation. The backend uses FastAPI, LangChain, Qdrant, and Supabase, and is deployed on Google Cloud. The user seeks feedback and collaboration, acknowledging limitations like cold starts and lack of websocket support.
I don't care at all about the product and this whole thing is probably all ai generated crap. But these screenshots are so bad. Buttons are all styled differently and hero is not even aligned.
yeah, i already centered the hero. After all, im especialize at backend
i can say that frontend is purely ai generated using antigravity. i can't write react with tailwind. its too much for me. the important parts for me in frontend layer are state management, token life cycle and security besides this, everything can be generated by ai
Repo: IntelliChat Repository
App: IntelliChat
Open for feedback and suggestions but I wont promise to implement all them because i'm busy at school now : >
Also open if anyone wants to contribute or break it.