AI agent governance for government and public sector
FedRAMP, NIST 800-53, the Executive Order on AI, EU AI Act: public sector sits in the highest-risk tier. Every citizen-facing agent needs a complete registry entry, risk classification, and audit trail before it touches production.
Government AI mandates are outpacing agency readiness
Agencies are deploying citizen-facing AI agents while compliance frameworks are still being written. The gap between mandate and implementation creates real risk: for citizens, for data, and for public trust.
Executive Order requirements demand an inventory of every AI system in use, risk assessments, and annual reporting. Most agencies have none of this infrastructure in place.
NIST 800-53 was written for traditional IT systems. Mapping its 1,000+ controls to autonomous AI agents that call external APIs and chain decisions requires a purpose-built layer.
Citizen data (Social Security numbers, benefits records, case files) flows through LLM prompts with no visibility into what leaves the agency boundary or gets cached by a model provider.
Regulatory frameworks for government
Pre-mapped requirements. Activate a framework and Roval tracks evidence per requirement.
Security and privacy controls for federal information systems, mapped to AI agent governance requirements.
Cloud service authorization for federal agencies, extended to cover AI agent deployment and model provider selection.
High-risk AI classification, conformity assessment, and transparency obligations for public sector AI systems.
AI risk management framework: govern, map, measure, and manage AI risks across the agency lifecycle.
International standard for AI management systems: governance, risk, and responsible AI development practices.
Trust service criteria mapped to agent governance, required by cloud service providers serving federal agencies.
Pre-built policies for government
Start from a template, customize the rules, and activate. Every policy enforces controls on your agents.
Detects Social Security numbers, benefits records, and citizen identifiers in prompts. Blocks sensitive data from reaching external model APIs.
Enforces network boundaries for agents handling CUI and classified data. Prevents data from crossing authorization levels.
Logs every agent decision, tool call, and data access with timestamps and user context. Exportable for IG and GAO reviews.
Validates that AI vendors and model providers meet federal procurement requirements: FedRAMP authorization, data residency, and pricing controls.
Requires documented impact assessments before deploying agents that affect benefits eligibility, case decisions, or public services.
Controls for agents that access data from multiple agencies: enforces data sharing agreements, purpose limitations, and audit logging.
Built for the audit that's already scheduled
Agency-wide agent inventory
Register every AI agent across the agency: framework, model, owner, risk tier. Search by natural language. Export the full inventory for IG and GAO reporting.
Real-time cost attribution
See which agents call which models, how many tokens they consume, and what they cost. Set budget alerts per bureau, per agent, per model.
Continuous compliance monitoring
Certifications expire. Configurations drift. Owners rotate. Roval detects it all within 15 minutes and alerts before your next IG review.
The full Roval platform
Agent Registry
Register every agent with framework, model, owner, risk tier, and dependency graph. Search by natural language.
Compliance
Certify agents against any framework with per-requirement evidence tracking. Auto-expiry by risk tier. Drift detection every 15 minutes.
Observer & LLM Monitor
Capture every tool call and LLM request. Flag PII and policy violations in under 30 seconds.
Dashboard
KPI cards, compliance posture, drift alerts, and a live event feed, on one screen, no clicking around.
Explore Roval for government
Join the private beta. Full registry and compliance setup in under 10 minutes.