RAG / LLM integrations

Your docs, your data, your business logic — augmented by AI, not replaced.

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Generic ChatGPT doesn't know your processes, your contracts, or your code. LLM à une base documentaire pour qu'il réponde sur VOS données.">RAG (Retrieval-Augmented Generation) does. It's the layer that lets an LLM answer based on your data: internal knowledge base, technical docs, client contracts, codebase. I design and integrate the full chain — embeddings, vector store, prompt engineering, guardrails. Output: a useful assistant, not a hallucinating parrot.

Tarif

From

4 500,00 €

Response within 48 business hours.

Included

✓ Audit of data and priority use cases (without it, you pay for useless POC)
✓ Ingestion pipeline + chunking + embeddings adapted to your corpus
✓ Vector store (Postgres/pgvector, Qdrant or Pinecone depending on volume)
✓ Query API + minimal UI (chat, search, action)
✓ Eval framework: we measure answers instead of "seems to work"

FAQ

Frequently asked questions

Depends on the case. GPT-4o / Claude / Mistral in hosted API for max quality. Llama / Qwen / Mistral in self-hosted (Ollama, vLLM) when confidentiality or cost demand it. I help you decide.

No data is sent to an external provider without your explicit validation. If confidentiality is critical, we switch to self-hosted from the POC.

No. The most interesting use isn't the chat but the action: agent that summarizes your support tickets, classifies your contracts, pre-fills your quotes from your history. Chat is a wrapper, the real gain is elsewhere.

From ~30€/month for light self-hosted use, to several hundreds in hosted API depending on volume. We estimate upfront and optimize prompts to limit tokens. No surprise on the bill.

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RAG / LLM integrations

From 4 500,00 €

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Response within 48 business hours.