Enterprise RAG System
A full-stack AI application implementing Retrieval-Augmented Generation (RAG) to allow enterprises to query their internal documents securely using large language models.
Project Image /projects/rag.png
Overview
Built with TypeScript, this system ingests, chunks, and vectorizes complex documents, storing embeddings in a high-performance vector database. It leverages modern LLMs to generate highly accurate responses, grounding all answers in the provided enterprise knowledge base to eliminate hallucinations. The interface is highly optimized for speed and reliability, featuring real-time streaming responses and conversation memory.
Technologies
- TypeScript
- Next.js
- Vector DB
- LLMs
- RAG
- TailwindCSS