I will build a custom rag pipeline and ai agent with fastapi and pgvector

Are you looking to integrate custom data into Large Language Models (LLMs) with high precision and low latency?

I build robust, production-ready Retrieval-Augmented Generation (RAG) systems and Agentic AI workflows tailored for your business needs.

What I Offer:

- Custom RAG Architecture: Document chunking, embedding generation (Cohere, OpenAI, Jina), and vector storage.

- Vector Databases: PostgreSQL (pgvector), Pinecone, or Qdrant integration.

- Hybrid Search: Dense + Sparse search for maximum retrieval accuracy.

- Backend Integration: High-performance REST APIs built with Python & FastAPI.

- Autonomous AI Agents: LangGraph workflows for complex, multi-step tasks.

- Clean Code & Docs: Fully typed (Pydantic), documented, and Dockerized code.

Tech Stack:

Python | FastAPI | PostgreSQL / pgvector | LangChain / LangGraph | Docker | OpenAI / Cohere

How We Work:

1. Contact me with your requirements before placing an order.

2. We define the project scope, tech stack, and deliverables.

3. I build, test, and deliver the system with step-by-step instructions.

Let's turn your data into an intelligent AI system. Send me a message to get started!