How we work

Scope the work before the build starts.

Most teams start with a diagnostic. We map one repeated loop, define what the system may do, set acceptance criteria, and separate production support from the initial build.

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AI Readiness Assessment

2 weeks

We pick one workflow, define the operating baseline, and say where AI belongs and where it should stay out.

Walkthrough of your current workflow
Honest assessment of what AI can and cannot do here
A short written report with a rough order of priority
One or two pilot ideas scoped to what we saw

Best for: You are not sure where AI fits and do not want to waste money guessing

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Pilot Build

4–8 weeks

Deploy one bounded workflow with acceptance criteria, human review, monitoring, and an agreed owner. Expand only after the first version works in the day-to-day operation.

Weekly demos so you can course-correct early
Deployed on your infrastructure, not ours
Monitoring so we know when it breaks
Documentation written as we go, not after

Best for: You have a specific pain point and a budget to test whether AI fixes it

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Ongoing Support

Monthly

The system is live. Now it needs to keep working. We handle the fixes, the model drift, and the things you should not have to think about.

A named route for fixes and incidents
Checks when the data or model changes
Monitoring for workflow failures
A regular review of usage and next steps

Best for: You shipped something and need it to stay reliable without hiring a full team

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