The Diagnostic
Two weeks of frank scoping inside the institution. We map the workflows that actually compound, the leakage points that don't, and the data that already exists but isn't yet trusted.
Automation is not a feature. It is the operating system we install inside an institution. The eight plays below are the moves we run, in the order we run them, against the workflows that compound.
Two weeks of frank scoping inside the institution. We map the workflows that actually compound, the leakage points that don't, and the data that already exists but isn't yet trusted.
We pick one workflow with a measurable outcome — not the most strategic one, the most teachable one. We ship it to production in eight to twelve weeks, with the operator's name on the dashboard.
Once one workflow is live, we wrap it in a continuous audit layer. Every accrual, every decision, every model output is logged, sampled, and reviewable.
Sub-minute anomaly detection on the inflows and outflows that matter. Alerts go to the operators who can actually act on them, not to a generic ops inbox.
Document classification across the long tail of templates the institution actually receives. The classifier learns from corrections; the corrections become training data; the loop closes.
Briefings, queues, and decision surfaces for the operators and principals who consume the output. Citation-grounded, never opaque, always traceable to source.
We train the institution's own engineers and analysts to operate, extend, and audit the system. The goal is not vendor lock-in — it is institutional capacity.
Quarterly reviews against the outcomes set in the diagnostic. Plays compound — each new workflow benefits from the audit, classification, and decision layers already in place.
Two weeks of frank scoping inside the institution. We map the workflows that actually compound, the leakage points that don't, and the data that already exists but isn't yet trusted.
We pick one workflow with a measurable outcome — not the most strategic one, the most teachable one. We ship it to production in eight to twelve weeks, with the operator's name on the dashboard.
Once one workflow is live, we wrap it in a continuous audit layer. Every accrual, every decision, every model output is logged, sampled, and reviewable.
Sub-minute anomaly detection on the inflows and outflows that matter. Alerts go to the operators who can actually act on them, not to a generic ops inbox.
Document classification across the long tail of templates the institution actually receives. The classifier learns from corrections; the corrections become training data; the loop closes.
Briefings, queues, and decision surfaces for the operators and principals who consume the output. Citation-grounded, never opaque, always traceable to source.
We train the institution's own engineers and analysts to operate, extend, and audit the system. The goal is not vendor lock-in — it is institutional capacity.
Quarterly reviews against the outcomes set in the diagnostic. Plays compound — each new workflow benefits from the audit, classification, and decision layers already in place.
The ninety day commitment: in the first ninety days of any engagement, we ship one production workflow with a measurable outcome on a dashboard the operator already trusts. No exceptions.