I will design a Retrieval-Augmented Generation (RAG) system powered by OpenAI, LangChain, and vector databases (Pinecone, Weaviate, MongoDB, FAISS, etc.) to deliver precise, reliable, and contextual answers.
- Custom AI chatbot trained on your PDFs, Docs, or databases
- Retrieval-Augmented Generation (RAG) pipeline
- Vector database setup (Pinecone, MongoDB, FAISS, or others)
- API integration (OpenAI, Claude, Mistral, or Llama-based models)
- Backend-ready Python code (FastAPI/Flask)
- Deployment on Heroku, AWS, or Vercel if needed
Use cases:
- Company knowledge-base bots
- Legal/finance document assistants
- Customer support chatbots
- Research or academic assistants