Civil service · programs · digital services
Public sector programs run on trust. When an agent makes a decision that affects a citizen, the chain of custody for data, model version, and policy must be legible to your IG, GAO-style bodies, and the public record as law requires. SoverAI is designed for that standard — not for a product demo in a skunkworks team.
IN / EU / US
Common pilot geographies
IRAP
AU-relevant pattern
FedRAMP
US public cloud path
IR
Joint incident posture
Regulators expect the same level of control over AI as for core systems — with clearer lineage and data boundaries than most cloud-native stacks default to.
Benefit and enforcement copilots must reference the right rule as amended — not a Wikipedia summary. Your knowledge graph and official sources are the only allowed retrievers.
Some workloads will never sit next to your digital services stack. The architecture must support distinct trust zones and cross-domain patterns your security team already use.
Disparate impact and contestability are program risks, not model metrics. The platform must make human review the default for certain classes of decision.
A single control plane: jurisdiction-first routing, agent guardrails, and evidence-grade audit you can hand to a supervisor without re-architecting your estate.
Patterns we see in diligence and architecture reviews with regulated customers — not exhaustive, but designed to be concrete for internal steering committees.
Mapped to the frameworks your legal and second-line teams already use — with exportable evidence bundles per region.
Regulatory context: National and supranational expectations in each market you serve — we do not sell a one-line ‘compliant in all countries’ claim. We work with your programme office to document the right boundary for the mission.
We will map your data classes, model catalog, and regulator expectations to a deployable control-plane design — with exportable artifacts for legal and security stakeholders.