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Fiverr Pro
English
$
USD
I will build a rag ai chatbot over your documents, data, or website
Jeffrey C
About this gig
I build retrieval-augmented (RAG) chatbots that answer questions over YOUR content docs, PDFs, a knowledge base, a website, or a database with real source citations, not hallucinations. The bot retrieves the relevant passages before it answers, so responses stay grounded in your data.
I've built a persistent-memory AI assistant from scratch: retrieval over a knowledge graph with thousands of nodes, context injection, and Claude/OpenAI orchestration. I know where RAG breaks bad chunking, weak retrieval, no evals and how to keep answers accurate. Behind that: 20+ years architecting enterprise systems (Fortune 500, defense) and graduate physics.
What you get:
- A chatbot grounded in your data, with source citations
- Proper chunking, embeddings, and a vector store (Pinecone, Chroma, pgvector your choice)
- Claude or OpenAI under the hood
- Clean, documented code your team can own and extend
- Straight talk on what RAG can and can't do for your use case
Message me before ordering with your data type, rough volume, and stack, and I'll confirm the right package.
Get to know Jeffrey C
Jeffrey C
AI Integration Engineer, LLM, RAG, Claude and OpenAI APIs, 25 Year Architect
- FromUnited States
- Member sinceJul 2026
Languages
English
I'm a physics-educated software engineer who builds LLM-integrated systems — RAG pipelines, agentic assistants, and Claude/OpenAI API integrations — on top of 25 years architecting enterprise-scale software (Fortune 500 insurance, defense). Recently I built a persistent-memory AI assistant from scratch: multi-agent, with a temporal knowledge graph, retrieval-augmented context, and Claude API orchestration. I bring production engineering judgment — CI/CD, DevSecOps, containerized delivery — so AI features actually ship and hold up. I'll tell you what's possible and what isn't, up front.
FAQ
What kind of data can the chatbot use?
PDFs, Word/text docs, a website, a knowledge base, a database, or an API. Send me a sample and I'll confirm what's workable.
Will it make things up?
No — it retrieves the actual relevant passages from your data before answering and cites sources, so it stays grounded instead of hallucinating.
Do I need an API key?
Yes, your own Anthropic (Claude) or OpenAI key. You keep control of usage and billing; I never expose it.
Do I get the source code?
Yes, on every package — clean, documented code your team can own and extend.
Which vector database do you use?
Your choice — Pinecone, Chroma, pgvector, or another. I'll recommend one based on your scale and stack.
