I will build an ai saas with rag, embeddings and vector search

Most AI gigs sell you a wrapper around an API key. This is a product: your own data, your own retrieval, your own app.

I build the whole stack. Documents in, embeddings and a vector index behind them, retrieval that returns sources, and a real web app on top that your customers log into.

WHAT YOU GET

Ingestion for PDFs, docs, sites, Notion or your database

Chunking, embeddings and a tuned vector index

Answers with citations, so users can check the source

Streaming chat UI, auth and document upload

Evals so you can prove quality instead of guessing

Cost and token controls, plus rate limiting

Clean TypeScript, documented, deployed and yours

STACK

Next.js, Node, TypeScript, pgvector, Pinecone, Qdrant, LangChain, the Claude and OpenAI APIs, Postgres, Stripe and Vercel

I have 65 five-star reviews and I build full stack, so the AI part actually ships inside a working product rather than a notebook.

Tell me what data you want it to answer from and I will tell you if RAG is even the right answer for you.