Work happens
People use AI in the real conditions of their jobs.
The enterprise control plane for AI
Make AI work for the way we work together.
AI is already inside approved tools, vendor software, team habits, and quiet workarounds. No one has the whole picture, yet decisions about it are already shaping how people work.
Kedai learns from AI work and continuously improves what comes next.
What did we learn?Peoplebring the contextWorkAI joins inUnderstandingwhat helped?Next decisionpeople choose
The work creates the signal. People decide what happens next.
Why Kedai
AI did not arrive in one place.
Across an enterprise, AI rarely arrives as one program. It appears wherever people find a way to move work forward. Sometimes by plan, sometimes by accident, and often long before policy catches up.
That leaves leaders, operators, and the people doing the work with different pieces of the same story. One group sees risk. Another sees efficiency. Another sees a tool that still needs three workarounds to be useful.
Kedai brings those perspectives together so the organization can understand what is happening, decide what deserves attention, and learn whether a change actually helped.
The idea
Learning from the work should improve what happens next.
Kedai follows the story past the AI answer. It connects what was accepted, changed, retried, or worked around with the context behind it. Over time, those moments reveal where AI is helping and where the surrounding system is getting in the way.
That understanding stays connected to the people closest to the work.
What gets examined is the way the work is set up, not the person doing it.
People adapt
Edits, retries, and workarounds reveal where the approved way helps and where it falls short.
Kedai connects the pattern
Repeated friction and useful adaptations become evidence for what should change.
The organization improves
Kedai works within the limits the organization has set, then measures whether the change helped.
Kedai connects evidence to the next decision and measures what follows. The organization decides how much authority Kedai has to act.
Help us shape Kedai.
We're still early, and we're talking with people who are trying to understand AI across a real organization without losing the judgment and context that make the work work. If that sounds familiar, we'd like to compare notes.