I will build a custom rag retrieval augmented generation system for your data

YOUR DATA + AI = A KNOWLEDGE SYSTEM THAT ACTUALLY UNDERSTANDS

Generic ChatGPT doesn't know your internal documents, product manuals,

or proprietary research. RAG (Retrieval-Augmented Generation) bridges

this gap letting AI answer questions based on YOUR data.

WHAT I BUILD:

• Document ingestion pipeline (PDFs, Word, websites, databases, APIs)
• Smart chunking and embedding strategy optimized for your content type
• Hybrid search (semantic + keyword) for maximum accuracy
• Citation-grounded answers every response shows its source
• Customizable UI (chat interface, API endpoint, or Slack/Teams bot)
• Handles 100,000+ documents with sub-second search

TECH STACK:

LangChain LlamaIndex ChromaDB Pinecone Qdrant Weaviate

DeepSeek OpenAI Qwen FastAPI Streamlit Next.js

WHY ME?

• Built RAG systems for legal, medical, e-commerce, and education
• Optimize for accuracy I measure and improve retrieval precision
• Cost-efficient I use DeepSeek embeddings (95% cheaper than OpenAI)
• Full documentation included your team can maintain it

️IMPORTANT: RAG projects vary significantly in scope. The prices above are

starting points. Message me with your document volume and use case for an

accurate quote before ordering.