For Government
Pilots are easy. Production is the job
Most public sector AI dies between the demo and the deployment. We build for that gap first.
01The real failure point
The demo always works.
Then it meets the security review. The records retention schedule. The accessibility requirement. The integration with a system older than the staff maintaining it. The contracting officer who's never bought anything shaped like this.
That's where public sector technology dies, whether or not the technology was any good.
We start at that stage instead of arriving at it.
02What we deploy
Workflow automation, in production
01
Workflow automation, in production.
The backlogs consuming your capacity: public records and FOIA, permitting and licensing, grants administration, eligibility review, constituent contact. Baseline captured before, results measured after.
02
Engineering teams.
Legacy integration, custom builds, data migration, and the connective work nobody else takes on. Accessible and auditable by construction, not retrofitted after an audit.
03
Governance you can defend.
Acceptable use policy, model inventory, risk framework alignment, vendor evaluation criteria, and the documentation trail oversight will ask for.
04
Accessibility as infrastructure.
Continuous monitoring and remediation through Stativ, so compliance is a system rather than a scramble.
05
Workforce capability.
Role-specific training built for public sector work and constraints. Your team should run and extend what we build.
03How we work
Deploy, then leave capability behind
01
We deploy, then we leave capability behind.
Every engagement ends in something running and a team that can run it.
02
We design for the constraint, not around it.
Security, accessibility, records, and procurement shape the build from week one.
03
We speak procurement.
Fixed scope, defined deliverables, and documentation your contracting shop can process without a translation layer.
04
We measure against a baseline.
If we can't show what changed, we didn't do the work.
04Our practices
Two practices, one standard
Government AI Performance OS
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