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N° 47.512° / 2.347°  ·  paris  ·  lyon  ·  genève  ·  tunis  ·  bruxelles  ·  luxembourg[ index ] /01  2026

// AI Consultant · Forward Deployed Engineer

AI&Datastrategyconsultant·ForwardDeployedEngineer.Fromstrategicvisiontooperationaldeployment.Noisolatedprototypes.Istructure,build,anddriveadoptionofData&AIcapabilitiesthatembedinoperationsandgeneratemeasurableresults.

scroll  ·  conseil  ·  audit  ·  déploiement ·  formation
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result guarantee

(1) If agreed objectives are not met, I extend the engagement at no additional cost.

Claude AI
OpenAI
Mistral AI
LangChain
LangGraph
LangSmith
LiteLLM
HuggingFace
dbt
Snowflake
Databricks
Airflow
Kafka
AWS
Google Cloud
Microsoft Azure
Kubernetes
Docker
Python
TensorFlow
Scikit-learn
FastAPI
PostgreSQL
Grafana
Streamlit
n8n
Terraform
WandB
Cursor
Notion
Claude AI
OpenAI
Mistral AI
LangChain
LangGraph
LangSmith
LiteLLM
HuggingFace
dbt
Snowflake
Databricks
Airflow
Kafka
AWS
Google Cloud
Microsoft Azure
Kubernetes
Docker
Python
TensorFlow
Scikit-learn
FastAPI
PostgreSQL
Grafana
Streamlit
n8n
Terraform
WandB
Cursor
Notion
// what I do

How I help

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// 01 · Strategy

Accompanying your AI strategy

Define where AI creates real value in your organisation. Ambition, use case prioritisation, decision roadmap and leadership alignment — before writing a single line of code.

AI vision & ambitionUse case prioritisationDecision roadmapLeadership alignment
Discuss your AI strategy →
// 02 · Forward Deployment

Forward Strategist Deployment

I embed directly in your organisation as an AI Director on mandate: vision, trade-offs, execution. The benefits of a CDO without the delay of a hire.

Embedded in your teamsFast strategic decisionsVision & execution alignedKnowledge transfer
Explore this engagement model →
// 03 · LLM & RAG

AI systems in production

From prototype to production: RAG architecture, LLM, agents, evaluation and MLOps. Robustness, security and observability included.

Modular RAG architectureLLM evaluation & qualityMLOps & observabilityGDPR compliance
Discuss an LLM project →
// 04 · Diagnostic

AI audit & scoping

Before investing, understand where you stand. Data and AI audit, risk mapping, prioritized roadmap.

Full current state reviewRisk mappingPrioritized roadmapMeasurable success criteria
Request an audit →
// 05 · Data

Pipelines & Data Platform

Reliable data foundations: ingestion, transformation, quality, governance. Lakehouse or cloud-native architecture based on your constraints.

Production pipelinesMonitored data qualityOptimized costsAutonomous teams
Build the data foundation →
// 06 · Architecture

Architecture & technology choices

Target architecture, technology trade-offs, business alignment and regulatory constraints. Documented decisions that hold in production.

Architecture blueprintDocumented ADRsSecurity/GDPR complianceTeam standards
Frame the architecture →
// 07 · Agents

AI agents & orchestration

Design and deployment of autonomous AI agents: multi-agent orchestration, tool integration, persistent memory and production supervision.

Multi-step agentsReliable orchestrationError handlingMonitoring & traces
Design an AI agent →
// 08 · Training

Training & skill development

445+ people trained in data and AI methods. Custom workshops, intensive bootcamps, technical team coaching.

Custom sessions, year-round
Custom programReal-world casesTracking & evaluationCertification possible
Talk about training →

// REALITY

Data wasn't your problem yesterday. That's fine.

Not doing it yesterday was a choice.

Not doing it today is a risk.

Not doing it tomorrow is being replaced.

Most organisations that reach out think they have an AI problem. 7 times out of 10, it's a data problem first: scattered data, no pipelines, no governance. I start there. Then we deploy.

Data architecture and AI deployment environment

// WHAT I DO

Scoping.Deployment.Support.

Many of you are looking for someone to deploy Claude, Copilot or ChatGPT in your organisation right now. I do that. But if your real issue is structuring data before layering AI on top, I do that too. I scope, I size, I deploy, I train your teams, and I stay until autonomy.

I deploy what they build.

anthropic

Claude

Workspaces, prompt libraries, Cowork, Claude Code, governance.

mistral ai

Mistral

On-premise, cloud, fine-tuning, La Plateforme, sovereign AI.

openai

ChatGPT

Enterprise, API, GPTs, Copilot Studio, data pipelines.

microsoft

Azure

M365 Copilot, Power Platform, Azure OpenAI, change management.

ecosystem

Open stack

LangChain, n8n, Make. Multi-model, RAG, agents.

FOR AI VENDORS

You build the models. I bring them to production in your clients' organisations. On-site or remote, France, Switzerland, Belgium, Luxembourg.

FOR ENTERPRISES

You need one person to own the AI rollout end to end. No agency, no 200-slide consulting deck. From scoping to skills transfer.

// projets

Work

Delivered architectures and systems in production.

View all projects →
Python 3.11FastAPIPostgreSQL + pgvector

MyHanout AI

AI copilot for local shops — demand forecasting, explainable restocking, invoice OCR and management from WhatsApp / Telegram / Slack. Multi-tenant, GDPR, human-in-the-loop.

Next.js 14TypeScriptClaude (Sonnet)

DealRoom Sentinel

AI Tech Due Diligence agent on M&A data rooms: ingests the data room, produces a sourced and scored Red Flags Report, and opens an anti-hallucination Q&A — every answer cites its source.

Next.js 15TypeScriptTailwind v4

Be-Ru

Be-Ru (Gradient Learning OS) — the OS for adaptive education: an AI-native, white-label learning-intelligence platform centered on the learner (Digital Human Twin), replacing the whole stack (LMS, quiz, analytics, tutoring, community).

Next.jsMilvusPostgres

Academic Knowledge RAG

Secure RAG assistant centralizing regulations, syllabi and procedures for higher education — faster document retrieval and full compliance traceability.

KafkaFlinkPython
Protected

Crowd Flow Optimizer

Real-time prediction and orchestration engine to optimize crowd flows and reduce congestion points during mega-events.

Detailed case study available upon direct contact.

05
KafkaFlinkPython
Protected

Smart City Command Center

Real-time urban supervision platform centralizing IoT, mobility, energy and security to operate a smart city from a unified dashboard.

Detailed case study available upon direct contact.

06

// latest articles

Blog & Reflections

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Insights·29 Mar 2026

Cognitive debt: the threat no one sees coming

In 2025 we talked about technical debt. In 2026 the real risk is called cognitive debt — the accumulated cost of poorly managed agent interactions, context loss, and unpredictable behaviors.

Read →
Insights·24 Mar 2026

The Hanoutier — How AI Created the Most Formidable Merchant in History

The Hanoutier — the neighborhood store owner who single-handedly manages purchasing, sales, logistics and customer relations — is the best metaphor for the AI solopreneur. Here is why juniors are better positioned than seniors to become the Hanoutiers of the digital era.

Read →
Engineering·22 Mar 2026

MCP: the quiet protocol changing how agents access data

Model Context Protocol flies under the radar but its adoption by Anthropic, OpenAI and enterprise vendors makes it the missing integration layer for production agents.

Read →
Insights·17 Mar 2026

AI in Higher Education Summit : what Paris is saying about the future of universities

Sold out, waiting list open. This summit brings together in Paris on March 17 and 18 the decision-makers who will define how 11 million European students learn in five years. What the program reveals, what I expect from each session, and why I will be there with my camera for both days.

Read →
Insights·15 Mar 2026

Agentic AI doesn't scale without clean data

67% of companies have deployed generative AI. Only 20% trust their analytical capabilities. The gap isn't a model problem — it's a data foundation problem.

Read →
Insights·14 Mar 2026

What CIOs still don't understand about AI agents

Agents are not improved chatbots. They're autonomous processes with memory, tools, and the capacity for action. The CIO who treats them like a standard IT project will be outpaced by their own vendor.

Read →

A project. A constraint. An outcome to define together.

I take engagements where impact is measurable and decision-makers are aligned. If that is your situation, let's talk.