Werk 09 — who carries it
An AI feature is a product decision wearing a model. The engineering that decides whether it survives contact with production is upstream and downstream of the model: the data it is fed, the evaluation that gates it, and the trace it leaves.
The offer
Models in production behind a real decision, with the lineage, evaluation and governance a regulated estate has to show — not a pilot that never left the lab.
Use cases scored on value, feasibility and risk, with the two or three that justify a platform investment identified and sequenced.
Generative or predictive models integrated into the product path, with retrieval, prompts or features engineered against the real estate.
Training, versioning, deployment, monitoring and rollback, so a model in production is an operated asset rather than an artefact.
Golden sets, offline and online evaluation, explainability, bias review and the governance record an auditor can read.
Use-case portfolio, data readiness verdict, platform decision.
Architecture, vendor arbitration, governance and risk posture.
The AI portfolio delivered and operated in production.
State of the proof
Experiences that prove it
Sub-capabilities and evidence
Publishable figures
Questions
- What has the collective actually shipped?
- A blockchain parametric flight-delay insurance product built at AXA and taken to market in two and a half months, on a group digital and big-data estate that was industrialised into a software factory in the same mandate. A conversational AI platform at Orange Business carrying 149 user paths. An AI conversational recruitment SaaS built from scratch at Peetchr, carrying a French DeepTech label.
- What does the AI work depend on?
- The data werk, always. A model on an ungoverned estate produces confident output from unverified input, which is worse than no model at all — it launders a data problem into a decision. AI mandates therefore start on the data platform and the lineage, not on the prompt.
- What is deliberately not claimed here?
- MLOps tooling and fine-tuning are declared, not proven: they are in scope for a mandate and no published case carries them yet. Model research is out of scope entirely. The collective applies and governs models; it does not build them.