From experimentation to adoption: deploying AI agents in production in 4 weeks
Most AI projects die as demos. Here's the method we use to go from a use case to real, measured adoption — in a month.
The real blocker isn't the tech — it's adoption
In most companies the reality is the same: Copilot here, Gemini there. Everyone with their own tool, nobody capitalizing, no governance, no measurement. Technology is almost never the blocker — adoption is.
An agent that dazzles in a demo but that nobody opens on Monday morning has created no value. So our starting point is the opposite of many projects: we start from real usage, not the demo.
Week 1 — Diagnostic and wiring into your real data
We identify 1 to 3 high-impact use cases in your teams, look at your data and tools (Teams, SharePoint, Slack, Drive, SAP…), and wire a first agent to your real data — not a test dataset.
That constraint changes everything: from the first week, what you see runs on your own material, not an idealized scenario.
Weeks 2-3 — Iterate with ambassadors, set the governance
We first equip a small circle of volunteer ambassadors, trained to test and validate the use cases. It's a deliberate choice: we build with the people who'll use the agents, not for them.
Governance rules — permissions inherited from your tools, per-request traceability, European hosting — are set before any rollout. Security isn't a layer bolted on at the end; it's the frame of the pilot.
Week 4 — Production and ROI measurement
Every pilot use case is built to go straight to production: nothing built is thrown away. We then measure the real gain — time saved, win rate, volumes handled — use case by use case.
And above all: if the ROI doesn't follow, we don't deploy. A systematic ROI approach also means being able to say when AI isn't the right answer.
What it looks like, concretely
Applium (SAP consulting firm): 90% adoption in 29 days. DataValue Strategy (EPM consulting): up to 70% time saved on meeting notes, delivered same-day.
The common thread isn't the tool — it's the method: the right use case, the right data, the right measurement. We're vendor-agnostic too: certified on Claude and Microsoft Copilot, partners with Dust, OpenAI and others. Because every company is different, and guaranteeing adoption starts with choosing the solution that truly fits your situation.