The Physical AI Stack maps the architecture. The Hyperion Lifecycle drives the delivery. Every engagement is anchored in both — built from 17+ years of production experience.
Most AI engagements fail because they lack both a technology framework and a delivery discipline. The Physical AI Stack maps the six layers from physical sensor to autonomous operation. The Hyperion Lifecycle ensures every layer reaches production in 90 days. Both frameworks were built from 17+ years at Cisco, Renault-Nissan-Mitsubishi, ABB, and Auralink — organizations where theory and production are two different departments.
Two core frameworks — the Physical AI Stack and the Hyperion Lifecycle — anchor every engagement. Each service adds its own structured methodology, built from production experience.
HOW to architect Physical AI systems
A six-layer model for making physical infrastructure AI-native. From sensor data capture to autonomous fleet orchestration. Used to architect Auralink: 400+ microservices, ~20 AI agents, 78% autonomous incident resolution.
HOW to deliver AI projects to production
A six-phase methodology ensuring every AI initiative has a production path. Built at organizations where pilot has an expiration date. Every phase has clear graduation criteria: ship, pivot, or kill in 90 days.
HOW European SMEs go from AI confusion to AI capability — same method, compressed for SME timelines
The Hyperion Lifecycle adapted for small and medium enterprises entering AI for the first time. Built from three government-appointed roles: French Government AI Ambassador ('Osez l'IA'), FranceNum Activateur, and La French Tech Athens Board Member. Same six phases, compressed timelines, budget-conscious execution. 90 days from diagnosis to production.
HOW to go from regulatory exposure to audit-ready compliance
A four-phase structured methodology for EU AI Act compliance. Built from building Aegis AI (automated compliance platform) and advising European enterprises through NIS2 and EU AI Act requirements. Every phase has clear exit criteria — no open-ended compliance theater.
HOW to secure AI systems and make AI secure your organization
A four-phase framework covering both directions: protecting your AI systems from adversarial attacks, and deploying AI to strengthen your security operations. Built from Achilles AI (210-rule static analysis for AI-generated code) and advising on NIS2 + EU AI Act dual compliance.
HOW to lead an AI transformation as an embedded executive
A four-pillar model for what embedded AI leadership actually means — not advisory slides, but operational leadership with accountability. Built from 17+ years in senior executive roles at Cisco, Renault-Nissan-Mitsubishi, and ABB, and from running 10 AI ventures simultaneously.
Focused engagements that answer a specific question. AI strategy, EU AI Act compliance, production audit — with clear deliverables and a fixed price you know before we start.
Best for:
Hands-on projects with milestone-based payment. I work alongside your engineering team to build and ship production AI systems. Payment tied to deliverables, not hours.
Best for:
Ongoing AI leadership at the level you need — from 2 days/month strategic advisory to embedded full-time transformation leadership. Senior AI thinking without the full-time executive salary.
Best for:
Hands-on training built around your real challenges — not generic case studies. Your team practices with your data, your systems, your constraints. They leave able to do it themselves.
Best for:
An honest conversation about your situation. I diagnose the real problem — not just the stated one. If I can help, I'll tell you exactly how. If I can't, I'll tell you that too. No pitch, no pressure.
I dig into the context your team doesn't have time to explain on a call. Stakeholder interviews, technical review, constraint mapping. The goal: understand the problem you actually have, which is rarely the problem you think you have.
A 2-3 page document — not a 60-page deck. Fixed scope, specific deliverables, exact price, clear timeline. You'll know precisely what you're getting and what it costs before you commit a cent.
Direct access to me throughout. Weekly touchpoints, async communication in between. No junior delegation — the person who wrote the proposal is the person doing the work. You'll never have to 're-explain' your business to a new face.
I deliver things that work in production — not 200-page strategy documents that collect dust. Code, architecture, runbooks, trained models, compliance documentation. Artifacts your team can use the day I leave.
Capability transfer is not an add-on — it's woven into the work. Your team learns as we build. When the engagement ends, you're more capable than when it started. 30 days of email support after delivery, included at no extra cost.
One operator. A fleet of AI agents. A team's throughput with one accountable mind.
There's no bench of juniors — there's a fleet of AI agents. The agents do the leverage work; the senior does ALL the judgment. The person on your discovery call is the person doing the work.
The Operating Loop
Intent
You and I set the outcome
Fan-out
Agents generate options and work in parallel
Judge
I select and adversarially verify every output
Integrate
I assemble and reconcile
Ship
Production, not slideware
Where Hyperion operates — and where we help you climb.
Hyperion runs at L3 — and helps your PM/Dev/QA teams climb L0→L3.
How I choose models for you — sovereign-first, frontier on merit.
Sovereign-first — the default
1a Mistral (EU-sovereign, supported) · 1b Open-weight (Llama/Qwen/Mixtral — when fine-tune/cost/control demands) · 1c On-prem / edge / air-gapped (the embedded & data-can't-leave posture)
Frontier-capable — on merit, never by default
Anthropic / OpenAI — only when a use case truly needs frontier the sovereign tier can't yet match
Decision scorecard
data residency · AI-Act/GDPR load · latency & edge constraints · capability ceiling · cost at scale · vendor lock-in · fine-tunability
My own apps run Mistral-only — the conviction proof. The ladder is what I recommend to you.