Mathias Dupey

Design and production deployment of two structuring AI systems. Operational productivity tripled for the functions concerned, without additional recruitment.

System 1

Autonomous editorial pipeline. Orchestrated agents covering the entire chain: brief ingestion, factual source verification (anti-hallucination safeguard), SEO gap analysis, editorial structuring, multilingual translation, and automatic publication on Webflow. Removed the bottleneck that was blocking organic acquisition.

System 2

Augmented community management. Real-time intent classification agent that qualifies each message and routes it to the correct queue, with systematic human escalation for sensitive cases rather than blind automation. Analytics back-office directly feeding product decisions. User data processed in compliance with GDPR.

Engineering firm specializing in the design and deployment of AI systems in production for French B2B companies, with compliance and sovereignty as basic requirements, not options.

Three areas: internal operations automation (workflows, document processing, reporting), commercial acquisition and qualification systems, integration of AI agents into existing business processes. AI Act and GDPR compliance considered from the architecture; data hosted in Europe and remaining the client's property at all times.

Fixed-price project model, results-oriented, not man-days, with a team dispatched as needed (AI, engineering, web, DevOps) and a dedicated AI hub for each client. Technical direction across the entire portfolio: architecture, stack choices, code review, recruitment, and orchestration of a bench of senior freelancers.

Design and production deployment of a next-generation RAG-powered CRM, where value lies not in data entry but in automated action. Agents analyze each incoming content (email, form, external signal), enrich the prospect profile from internal and third-party sources, generate a prioritized action plan based on the commercial context, and trigger follow-ups at the right time.

Central challenge: reliability in a noisy environment. Traceable recommendations back to their source, safeguards against erroneous actions, end-to-end latency controlled. Prospect data processing designed in compliance with GDPR. Agents orchestrated in Python on a dedicated RAG base, exposed via a Next.js commercial interface.