The engagement model
Diagnose first. Then deliver value every two weeks.
Most AI projects fail because they prescribe a solution before they understand the problem. We work the other way around. Every engagement starts with a short diagnostic and moves in visible cycles from there, with something to show you every day.
The rolling model
While case #1 is being supported and measured, case #2 is already in build. After the initial ramp, a new improvement ships roughly every two weeks, and each one is a separate thread you can start, pause, or stop on its own.
Diagnostic (one to two weeks, once). Our lead operator works directly with your team, on-site wherever possible, because sitting with people is the fastest way to see where the work really breaks. First with leadership, then in the field with the people closest to the work. You end with a ranked shortlist of the operational cases worth solving, scored on value and on how fast we can ship them, and agreement on which one goes first.
Build and deploy (two weeks per case). We build the agents, integrate them, and take the case live with your people trained on it. You see progress in a quick showcase every day, so there are no surprises at the end.
Support and measure (two weeks per case). We hold the system to a tight response standard while it beds in, and we measure the result against the baseline we agreed. This is where value gets confirmed.
Live and compounding. The case becomes your new normal. We monitor it, catch drift before you feel it, and keep it healthy. Fees begin here, tied to the value that has been confirmed.
Your data, handled properly
Built for teams that cannot afford a data incident.
SSO and SCIM. Least-privilege, read-only scopes. Encryption in transit and at rest. Human-in-the-loop on every risky action, with a full audit trail. Zero security incidents across every deployment to date.
Connect. We authenticate through your existing identity provider (Okta, Microsoft Entra, Google Workspace, Ping). You provision and revoke our access the same way you do for any employee. You always control who can log in.
Read. We take read-only access to the specific datasets we have agreed on, scoped to exactly what a case needs across your ERP, CRM, HRIS, and communication tools. Nothing outside that scope is touched.
Reason. Data lands in our secure workspace, encrypted in transit and at rest. Our agents read it, reason over it, and prepare the recommended actions. Every action that matters waits for a human to approve it.
Write back, on your terms. Results flow back to your action plans, your dashboards, or directly into your systems of record, under one of three control modes: full auto-write for low-risk actions, review-and-approve for the rest, or read-only display. You decide per workflow.
The commercial model, in full
Aligned with your P&L, by design.
We price the way an operator would want to be priced to. You should not carry the risk of whether AI works. We should.
The result is simple to reason about. We only win when you win, and we win less as the win becomes yours to keep.
How it works
A small fixed-fee diagnostic to start.
A defined, modest fee for the one-to-two-week diagnostic. You walk away with a ranked opportunity map you can act on, with us or without us.
Then a share of confirmed value.
Once a case is live and measured, our fee is anchored to a fraction of the uplift it has produced against the agreed baseline. Value we cannot confirm is value you do not pay for.
The fee reduces every year.
Our share is highest in year one, when we are doing the most work, and steps down each year after as the improvement becomes permanent. In the long run it settles to a small maintenance share for keeping the value alive.
Case by case, cancel any time.
Every case is its own thread. If one stops being worth it to you, we switch it off and you keep everything else. No single thread holds the relationship hostage.
Why our work lands
What makes this different from the last vendor.
Operator-first.
The person leading your engagement has run operations, not just advised on them. That is why teams talk to us openly and why the cases we pick are the ones that actually move the number.
Diagnose before we prescribe.
We earn the right to build by proving we understand the problem first. It is the single biggest reason AI projects succeed or fail.
Momentum that never drops.
A senior operator sits with your team while a dedicated engineering team works the same problem in parallel. Each day's findings come back as tested, working software the next morning.
We protect the value, not just ship it.
Most of the risk to an AI system shows up after go-live. We monitor continuously and fix issues before you notice them. Often you hear about a problem from us, already solved.