I will build a secure b2b rag pipeline and vector database

Are you ready to transform your proprietary data into a secure, intelligent knowledge base that your users can actually talk to?

I will architect a production-grade Retrieval-Augmented Generation (RAG) backend designed for speed and security. I specialize in building "private" AI systems that allow businesses to query their internal documents without exposing sensitive data to the public.

What's Included:

• Advanced PDF and document parsing
• Vector database setup (ChromaDB, Pinecone, or Weaviate)
• Semantic search and metadata filtering logic
• FastAPI backend with structured JSON outputs
• Secure data isolation for multi-tenant applications

Why Choose This Package:

• Strictly Engineering-First: No low-code wrappers, just clean Python and LangChain.
• Production-Ready: I deliver code that is ready to be containerized and deployed.
• Data Security: Focused on local embeddings and private VPC architectures.
• Scalable Design: Built to handle thousands of documents with high-performance retrieval.

Requirements:

• Sample data/documents (PDF, CSV, etc.)
• Preferred AI Model API Keys (OpenAI, Gemini, or Anthropic)

Contact me before placing an order to discuss your data structure and technical requirements!