A sealed sandbox where your team trials Microsoft Copilot, Copilot Studio, and Azure OpenAI on representative samples of your own data — before you commit a single license.
We're getting the next version of the ai experience lab polished so the upgrade ships sharper. In the meantime, our flagship AI Readiness Assessment is live and free.
Same team · same Microsoft AI stack · returning shortly
What the Experience Lab will do
Stop buying licenses on a hunch.
The AI Experience Lab is a sealed environment that lets your team actually use Microsoft Copilot, Copilot Studio, Azure OpenAI, and Power Automate against representative samples of yourdata — not a vendor demo dataset — before you commit a single license. The goal is to convert “maybe this will work for us” into a hard yes/no with named users, named workflows, and a measured before/after delta you can take to a budget conversation.
Each Experience Lab engagement runs in a short fixed window. We stand up the tenancy, ingest masked samples of your actual documents, contracts, tickets, or call transcripts, build the two or three agents that map to your top opportunities (we already ranked them in the free AI Readiness Assessment), and put real users in front of them. The output is a side-by-side comparison: baseline vs Copilot vs Copilot Studio vs Azure OpenAI, on time-to-complete, quality, and cost-per-action.
Until the lab is open for booking, the same evidence base — the workflows we’ve already piloted — lives in our case studies, our Copilot rollout consulting, and the Microsoft AI stack map we keep up to date. The same de-risking discipline shows up in the security posture page: your data never leaves the tenancy, and the sub-processor list is published.
Join the waitlist
We’re piloting with a small number of SMBs first. Add your email and we’ll send a single message when slots open — no drip blast.
Your data, your tenancy
Masked samples stay inside your Azure tenancy. We work as a guest, not a vendor.
Side-by-side comparison
Same workflow, four tools, measured time-to-complete, quality, and cost.
Fixed-window engagement
Two-week sprint, two or three agents, real users. No open-ended retainer.