Custom AI development
AI integration built like software: connected to your data, governed by guardrails, shipped to production. Agents, RAG, automation — built for your business.
Three months before the annual renewal date — i.e. before September 30, 2026. Renewal is automatic (clause 12.3).
AI, delivered like software
No throwaway POCs: AI integrations built, tested, and operated like a product.
AI integrated into your tools
Connecting AI to your existing stack — ERP, CRM, business platform — via controlled connectors (MCP).
RAG on your documents
An assistant that answers from YOUR content, with cited sources and role-based access control.
Agents & automation
Repetitive tasks handled under human supervision with full traceability.
Evaluation & guardrails
Evaluation harness, sensitive data filtering, audit log — before production.
Models & hosting
Proprietary API or open-weight models deployed on your infrastructure: the choice is made per use case.
Memory & context
An AI that knows your business: context, history, internal vocabulary.
From listening to a living product
Une méthode simple, lisible, sans effet tunnel.
Assessment
Use cases prioritized by impact × feasibility.
Scope
Data, guardrails, foundation architecture.
Build
Foundation + first use case, auditable code.
Production
Evaluated, monitored, optimized over time.
What you gain
Au-delà de la technique, des résultats concrets au quotidien.
AI that answers correctly
Grounded in your data, not in assumptions.
Costs controlled
Models chosen for the need, optimized context, caching.
A foundation you own
Code, memory, and governance belong to you.
What we’re asked most often
Et si votre question n'y est pas, on y répond de vive voix.
What's the difference with the Enterprise AI Core?
The Enterprise AI Core is our vision: the shared foundation (memory, context, governance). Custom AI is the engagement: we design and deliver your concrete use cases — often built on top of that foundation.
Which models do you work with?
Proprietary models (Claude, GPT, Mistral...) as well as open-weight models deployed on your infrastructure. The choice is made per use case — cost, confidentiality, performance — and remains reversible.
How long for a first use case?
After the assessment, a scoped first use case is typically in production within a few weeks — measured and monitored, not just demoed.
Will our data be used to train models?
No. No data is sent to third-party APIs without your agreement, and nothing is used to train external models.
Your first AI use case, in production ?
We start with an assessment: the highest-impact use cases, scoped and measurable — no commitment required.
Start with an AI Assessment