AI agents & workflow automation
Agents scoped to a task with a defined failure mode.
The problem
What usually brings people here.
A process that eats a person's week is a good candidate for automation right up until the agent does something confidently wrong at three in the morning and nobody notices until the reconciliation. The question is not whether it can do the task; it is what happens the day it gets it wrong.
What we do
How the work actually runs.
We scope the agent to a task with a defined blast radius, give it a defined failure mode, and put the approval step where the cost of an error justifies one. Every run is logged with its inputs and its reasoning so a human can audit it afterwards. The first increment is usually the narrowest useful slice, running alongside the manual process rather than replacing it.
How this runs
Design, develop, refine.
Design
Two to four weeks. We scope with the engineers who will build it, so the estimate comes from the people held to it.
Develop
Two-week increments, demoed to you, shipped behind flags. You see working software in week three, not a status deck.
Refine
The squad stays. Lead time comes down, the backlog gets shorter, and the same people know why every decision was made.
Proof lives on the work page.
We publish numbers per engagement, cleared by that client, rather than per service line. What is written up there is what we are allowed to show.
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