I will build a rag chatbot trained on your documents

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adam_vanss
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adam_vanss
Adam M

About this gig

Your docs, not generic chat.


I build RAG chatbots that answer from YOUR PDFs, websites, or databases - with citations. Chunking, embeddings, a vector store, and a grounded chat UI. You get source code, a runnable app, and a short handoff.


What you get:

  • Ingest PDFs, sites, docs, or a DB dump
  • - Chunking matched to your content
  • - Embeddings + vector DB (Pinecone, Chroma, Qdrant, Weaviate, or pgvector)
  • - Dense / hybrid search and optional reranking
  • - Chat API + web UI with source citations
  • - Prompts that refuse to invent facts when retrieval is empty

Stack: Python, FastAPI or Next.js, LangChain or LlamaIndex, OpenAI / Anthropic / local LLMs, Docker.


Process: you send sample docs + real questions, I ship an index + chat loop, we iterate on wrong/missing answers, then handoff.


To start: 5-20 sample files and 10 real questions. Message me if you need Slack, SSO, or a specific vector DB.

Get to know Adam M

Adam M

AI Engineer, RAG, ML and Agents

  • FromMorocco
  • Member sinceSep 2025
  • Avg. response time1 hour
  • Languages

    English, French, Arabic
I build production AI systems: RAG chatbots grounded in your docs, custom ML and deep learning models, generative AI apps, and tool-using agents. Python, LangChain, LlamaIndex, PyTorch, FastAPI. You get source code, evaluation, and a handoff - not a wrapped chatbot template. I will tell you if RAG, a model, or an agent is the wrong tool. Based in Morocco. English and French.