Jérôme Vetillard — About

Positioning

What is rare in this positioning is not each of these three dimensions separately — it is their coexistence within a single trajectory. Most AI medical experts have a computer science background and superficial medical exposure. Most clinicians interested in AI lack system architecture training. Most product strategists in healthcare don't have doctoral-level scientific training.

A performant AI system is not yet a deployable system. The real work lies between these two states.

Education

The training trajectory is intentionally pluridisciplinary — covering domains that don't communicate spontaneously and whose combination is the foundation of the Twingital Institute's approach.

20 years at Microsoft

Twenty years at Microsoft — from Global Solution Architect to Senior Industry Advisor Healthcare & Life Sciences — provided one rare asset: intimate, insider knowledge of how large organizations deploy — or fail to deploy — technology systems at scale in regulated environments.

Twenty years produced a central conviction: technology systems rarely fail for purely technical reasons. They fail because organizational architecture wasn't ready, governance wasn't defined, regulatory constraints were ignored until the last moment. The Twingital Institute's doctrine was born from this observation.

Today

VP R&D & Chief Product Officer · Qualees

At Qualees, the role covers product strategy, R&D architecture and management of research programs around TweenMe. This includes leadership of PREDICARE (territorial predictive medicine program, €3.5M, BPI France and GHT pre-validation) and 4 paid TweenMe POCs in real operational environments.

Scientific recognition of the Qualees work materialized notably through the Top 5% poster ranking at ISPOR Glasgow 2025 for the Smart Data Fertilizer algorithm in TweenMe.

Founder & Director · Twingital Institute

The Twingital Institute is the think tank founded to document, formalize and disseminate the doctrine of AI industrialization in regulated systems. It produces the RAISE Framework, research publications, doctrinal positions and cross-disciplinary explorations.

Approach and philosophy

A fundamental tension exists in the AI ecosystem, rarely named explicitly: the difference between a performant system and a deployable system. Algorithmic benchmarks measure performance under ideal conditions. They do not measure governance, traceability, resilience under degraded conditions, operator acceptability or regulatory compliance.

The Twingital Institute's approach starts from this tension. The RAISE Framework is the primary instrument: five pillars (Regulatory, Accountability, Interoperability, Safety, Explainability) that structure architectural decisions from design — not at certification phase.

Regulatory compliance added at the end of a project structurally generates non-compliant systems, or prohibitive remediation costs. It must be an architectural property — not a final audit.