AI Decision Infrastructure
The governance control plane for enterprise AI
The layer that evaluates AI outputs before they reach enterprise systems—so policy, risk, and governance checks happen in runtime, not after incidents.
Real-time guardrails
Detect and block unsafe AI outputs before they reach users.
Evidence-backed audits
Every AI decision produces traceable compliance evidence.
Continuous monitoring
Monitor AI risk, hallucinations, and regulatory exposure across jurisdictions.
Runtime governance · hAIniel
Try an AI governance simulation
Experience the system—not just the diagram. Preload a scenario or type a question; output mirrors how the governance layer decides (illustrative—wire to your engine when ready).
1,200+
Governance checks executed
74
Policies evaluated
8+
Jurisdictions supported
220ms
Avg. decision latency
Built for AI systems operating across regulated environments. Presets reflect governance evaluation contexts—risk signaling and audit-style outputs, not certification. Currently in evaluation across multiple jurisdictions.
This simulation mirrors the runtime governance checks hAIniel performs before AI decisions reach users or downstream systems—not a toy demo, but the same decision shape as production.
Connect to /api/governance/evaluate when ready—payload maps directly to this verdict block.
Product modules
Governance core, compliance, evidence, and AI safety.
Governance core
- Governance Console
Central operations view—status, escalations, and guardrail activity in one place.
- AI Risk Assessment
Structured assessments before production and after material changes.
- Policy engine
Configure rules, policy packs, and enforcement—RBAC and environment separation as you scale.
Compliance
- Compliance Monitor
Continuous checks against the frameworks you care about—not point-in-time only.
- Legal Verification
Citation and legal workflows for outputs that must stand up to review.
- Sovereignty & Control
Jurisdiction-aware controls so deployments stay within your boundary.
Evidence
- Audit Logs
Immutable-style trails—export-ready for GRC and regulators.
- Audit Reconstruction
Replay and search decision history to explain or defend outcomes.
AI safety
- Guardrails
Enforce input/output boundaries—block, rewrite, or escalate before unsafe or policy-violating content ships.
- Hallucination Control
Grounding and detection in the request path—ungrounded outputs caught early.
Platform
The hAIniel Platform
hAIniel provides a modular governance platform designed to support AI systems operating in regulated and enterprise environments.
Governance Engine
Evaluates AI outputs for policy compliance, hallucination risk, and regulatory context before execution.
Regulatory Context Engine
Maps governance checks to jurisdictional regulatory signals and policy frameworks.
Risk Intelligence
Analyzes AI outputs for hallucination indicators, confidence signals, and potential compliance exposure.
Audit Infrastructure
Generates structured audit evidence for every governance decision.
Deployment Layer
Supports sovereign, enterprise cloud, and private infrastructure environments.
Nations
Jurisdictions we support
Governance evaluation contexts span multiple jurisdictions for risk signaling and audit evidence.