Use-case scoping, Microsoft 365 Copilot, governed agents, Power Platform, IDP, hyperautomation, trusted cloud, governance and AI literacy—with proof of value and AI Act compliance from day one.
We qualify use cases, prove value in four to six weeks, then deploy under governance: identities, access rights, DLP, trusted cloud, and team training.
AI fits where business teams already work — M365, Dataverse, ERP, CRM, ECM — without rewriting the IT landscape or creating shadow IT.
From intelligent assistants to scoping workshops and Proof of Value (PoV), a service catalog dedicated to deploying artificial intelligence at the heart of business tools and processes.
Deploy AI where business teams already work
Use-case scoping, Microsoft 365 Copilot deployment and design of declarative agents in Copilot Studio, grounded in the organization graph via Microsoft Graph and the Semantic Index. Existing access rights apply without data duplication, and the transparency obligation under Article 50 of the AI Act is addressed from the design stage.
Identified, governed and accountable agents
Design of specialized agents triggered by event or conversation, with a first-class identity (Microsoft Entra Agent ID) and an explicit action scope: tools exposed via MCP, transactional actions on Dataverse and business APIs, human validation on high-impact steps. Each agent has an owner, a lifecycle, and an audit trail.
Replace Excel, Access, and shadow IT
Business application development on Power Platform and Dataverse — Canvas, Model-Driven and Code Apps in React and TypeScript — with a full application lifecycle: managed solutions, deployment pipelines, environment separation. Migration of Excel and Access estates, and RGAA 4.1 compliance when the sponsor is in the public sector.
Extract, validate and inject document data
IDP (Intelligent Document Processing) pipelines applied to orders, invoices, work orders, and contractual documents: extraction models trained on the client's documents, confidence thresholds, human validation for uncertain cases, business control rules, then reinjection into the information system. The steering KPI is the end-to-end processing rate.
Orchestrate processes end to end
Process modeling in BPMN 2.0, objectification via process mining and task mining, then automation of cross-application flows with production-grade guarantees: idempotence, error recovery, logging, and monitoring. AI building blocks integrate into existing chains — ERP, CRM, messaging, document management — without rewriting them.
The right level of sovereignty for each use case
Qualification of the sovereignty level actually required by the data processed, then architecture choice accordingly: EU Data Boundary and hosting in the France region, offerings undergoing SecNumCloud 3.2 qualification for the most sensitive processing, European models, HDS certification when the domain requires it. The structuring criterion is exposure to extraterritorial laws—not location alone.
Keep AI from becoming shadow IT
Governance framework grounded in recognized standards and instrumented on the platform: inventory of applications and agents, Managed Environments, DLP policies, Microsoft Purview, periodic access reviews. Enough to document compliance with AI Act obligations applicable as of August 2, 2026.
A regulatory enablement obligation before it becomes an adoption topic
Article 4 of the AI Act has required since February 2025 a sufficient level of AI literacy for the people concerned through our IA4D pathway. We design and deliver the matching programs for executives, business teams and technical teams: generative AI usage, prompt and context engineering, automation, AI-assisted development, MCP protocol and multi-agent systems. Skills assessment against Kirkpatrick’s four levels.
Count, track, and alert from the video stream
Multi-object detection and tracking on camera streams: people/flow counting and analysis, ByteTrack, occupancy rates, PPE compliance, warehouse container tracking, in-line quality control. Models trained on client data, edge inference to meet latency targets, evaluation against reference metrics for optimization.
Identify use cases worth investing in
Qualification of use cases on a value/feasibility matrix, estimation of total cost of ownership and payback time, trade-off between market solution and custom development, then a four-to-six-week proof of value with exit criteria defined upfront. At the end, a documented decision: industrialize, adjust, or stop.
Copilot, agents, Power Platform, IDP, trusted cloud, governance, and AI literacy—with proof of value.