I will build a secure rag chatbot for your documents with citations using langchain

Stop your AI from hallucinating. Start getting answers you can trust.

You don't need another generic "Chat with PDF" script. You need an Enterprise-Grade RAG (Retrieval-Augmented Generation) System that your employees can actually use for work.

I am an AI Engineer specializing in Secure Internal Search. I build systems that let you chat with your company data (PDFs, SQL, Notion, Sharepoint) without sending your secrets to the public web.

Why my RAG systems are different:

• Zero Hallucinations: I implement strict "Grounding" prompts. If the answer isn't in your documents, the bot says "I don't know" instead of lying.
• Source Citations: Every answer includes a link to the exact page and paragraph it came from (e.g., [Source: Employee Handbook, p. 12]).
• Data Privacy: I can deploy on your private cloud (Azure OpenAI, AWS Bedrock) or use open-source local models (Llama 3, Mistral) so your data never leaves your server.

What I Build: A full-stack application (Backend + Frontend) where you can upload documents and chat immediately.

My Tech Stack:

• Orchestration: LangChain / LlamaIndex
• Vector DB: Pinecone / Qdrant / Weaviate / Chroma
• LLMs: GPT-4o, Claude 3.5, Gemini Pro (or Local Llama 3)