AI strategy thatsurvives the pilot.
Most AI programs stall between the demo and the deployment. We work on the part that decides which way it goes — the use cases you pick, the governance around them, and whether your organization can actually operate what it builds.
Where we start
An AI readiness assessment across data, architecture, security, skills, and governance. The output is not a score — it is a ranked list of what is blocking value and what it would take to unblock each item.
Choosing the work
Use-case discovery run against operational reality: what the process actually costs today, what a model could plausibly change, what evidence would prove it, and what happens when the model is wrong. Use cases that cannot answer the last question do not proceed.
Governing it
Responsible-AI frameworks covering accountability, model oversight, human review, transparency, and regulatory posture — written so the people who own the process can apply them without a lawyer in the room.
