Sectors / Government & Public Sector
Sovereign AI deployment for entities where data cannot leave the building.
Public-sector AI mandates have moved from policy to execution. The gap is capacity: systems that meet sovereignty and data-residency requirements, and the engineering to deploy them in production.
Procurement timelines, sovereignty constraints, and a duty to demonstrate measurable outcomes against published strategies.
The work has to land inside the perimeter, with documented controls, and with the people who already run the systems.
AI conversations dominate the agenda. AI production dominates none of the budgets yet.
Where engagements typically start in this sector.
- On-Prem AI & LLM
Sovereignty is the constraint. The deployment posture defines what is possible everywhere else.
- AI Strategy & Readiness
Procurement and stakeholder alignment require a roadmap that ties to the published strategy.
- Managed AI Operations
Deployed systems need owned operations with controls, audit logs, and incident response.
Procurement-aligned phases. Viability study as Phase 1: model selection, infrastructure sizing, security posture, fixed scope. Production deployment as Phase 2, sized to the system. Managed operations follows handover.
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Start with the assessment.
A fixed-scope AI readiness assessment: your workflows, your data, your highest-ROI agent use cases, and a deployment roadmap. Two to four weeks.