I will build a custom AI agent or RAG pipeline for your project using LangChain, LangGraph, FastAPI, and your preferred LLM provider including OpenAI, Claude, or Gemini.

What you receive: clean, documented Python code, full LLM integration, vector database setup using Pinecone, ChromaDB, or FAISS, and a REST API built with FastAPI that is ready to plug into your existing application or workflow.

My background: I have 4 years of production experience building AI systems that handle 50,000 monthly users, 2 million document RAG pipelines, and APIs running at sub-200ms latency. I have fine-tuned Llama 3 models using LoRA and QLoRA and built multi-agent systems with tool use, memory, and Human-in-the-Loop flows using LangGraph.

What I can build for you: a single AI agent with tool use, a multi-agent orchestration system, a document Q and A pipeline over your own data, an LLM-powered REST API backend, or a voice AI pipeline using Whisper and ElevenLabs.

Process: you share your requirements, I confirm the scope and timeline, deliver the working code, and handle up to 2 rounds of revisions until you are satisfied.

What I need from you: a short description of your use case, your preferred LLM provider, and any existing data, documents, or APIs the agent should connect to.

Message me before ordering if you are unsure whether your project fits.