We turn one high-friction workflow into a system your team accepts.
Not a pilot. We stop if it isn't worth building.
AI pilots die between the workshop and the workflow. The pattern is usually the same.
[01]
The company can't move at the speed of AI.
You can ship a prototype in a week. Deploying it to a team takes a quarter. The quarter is the bottleneck, not the week. Every AI engagement that ignores this produces something that works in the demo and dies in the rollout.
[02]
The people weren't trained for the work AI leaves them.
AI absorbs parts of execution. The human role moves: people stop reviewing every routine output and start defining policy, resolving exceptions, carrying accountability, and improving the system. Most teams were hired, trained, and promoted for doing the work, not for running that layer.
[03]
The company runs on meetings, not systems.
AI can operate anything that has an interface. Most company work does not have one. Decisions sit in Slack threads, Google Docs, meetings, and someone's head. You can't point AI at that. You have to build the interface first.
[04]
The deployment was never in scope.
The deck lands. The partner leaves. The prototype needs owners, permissions, review flows, and operating metrics. None of that was priced, staffed, or built.
Work exists in the gap between these four failures and AI in production.
Control is not a feature we add at the end. It is how the system is built.
Three standalone entry points. None depends on the other.
[ I ]
5 to 10 days, fixed fee
You know AI should change this operation, but not yet what deserves rebuilding. We map the friction, choose the workflow with you, and write the acceptance criteria before anything is built. Diagnose ends with a clear decision: build a new system, embed an existing one, or stop. The map is yours either way.
Start with a diagnosis →[ II ]
2 to 4 weeks, milestone pricing
You know the operation and the outcome you need. You need a controlled system in production. We rebuild the workflow with your team and deploy it into real work, measured against acceptance criteria. If none exist yet, writing them is the first Build milestone, not a reason to start with Diagnose. The deployment milestone only invoices if it ships.
Start a build →[ III ]
time-boxed, scoped to the workflow
You already have a prototype, product, or internal system. It does not yet survive real usage. We turn it into something your team can run, measure, and improve. We stay inside the workflow long enough for the system to survive real usage. We help your team run the review queue, tune the system, handle exceptions, update the controls, and measure whether supervision falls without quality dropping. Then we hand it over. Your team owns the workflow. Off-ramp, not lock-in.
Talk about embedding →[01]
Sales prospecting.
Target accounts researched, scored, drafted, reviewed, and sent with evidence attached.
[02]
Support triage.
Tickets classified, summarized, drafted, and escalated according to your rules.
[03]
Reporting.
Weekly packs assembled from source material, with changes, risks, and open decisions highlighted.
[04]
Client briefing.
Account context, history, risks, and next actions prepared before the meeting, not after.
[05]
Internal knowledge.
Questions answered from approved documents, with sources attached and escalation when evidence is missing.
If your workflow is not on this list, that is what Diagnose is for.
And people on your team who understand how the system works, how to review it, and what can be changed without calling us back. That was the point.
A prompt library. A change management workshop with no technology attached. A 120-slide deck. An AI strategy that does not name the thing being built. An ungoverned demo. Hours.
Not ready to engage yet? The Room is the place to start.