One method, from scoping to deliverable.
Six phases that follow one another, each with a precise objective and documented deliverables.
Scoping and audit
ObjectiveUnderstand your situation and set measurable success criteria.
DeliverablesMapping of sources, uses and risks. Scope and roadmap.
Data industrialization
ObjectivePut the data foundation in place: collection, centralization and structuring.
DeliverablesArchitecture, connected sources, automated flows, quality controls.
Semantics and decision architecture
ObjectiveShare the same business definitions and prepare for analysis.
DeliverablesSemantic model, documented target architecture, management indicators.
Model design and deployment
ObjectiveBuild, evaluate and integrate the AI model on your data.
DeliverablesTrained and evaluated model, integration into your systems, technical documentation.
Governance and regulation
ObjectiveGovern data and AI: roles, rules, compliance.
DeliverablesRegister of uses, governance framework, GDPR and AI Act compliance file.
Handover
ObjectiveHand over the project and make it self-sufficient for your teams.
DeliverablesDocumented deliverables, skills transfer, reasoned decisions.
Our principles
Everything is documented
Every architecture, model and rule is described, so your teams can understand and evolve them.
Everything is auditable
You know what each component does, on which data and within what limits.
Your data stays yours
It is hosted in your environment, under the rules you define.
Each phase stands alone
An engagement can cover a single phase or all of them, depending on your starting point.
Contact
An engagement can cover one phase or the entire journey. Let's talk about your starting point.
Get in touch