AI Agent Governance

Policy enforcement. Not just policy documentation.

Define governance rules in YAML. Enforce them at the gateway — before your agents act. Prove every decision with cryptography.

The shift from monitoring to enforcement.

Traditional Monitoring

1Agent acts
2Action is logged
3Alert fires (maybe)
4Human investigates

CLPI Enforcement

1Agent requests action
2Policy evaluated at gateway
3Allowed or blocked instantly
4Proof generated automatically

Five pillars of AI agent governance.

Card Lifecycle & Policy Intelligence — from policy definition to cryptographic proof.

Policy Language

Define governance rules in YAML. Human-readable. Machine-enforceable. Version-controlled alongside your code.

# mnemom-policy.yaml
version: 1
rules:
  - action: access_pii
    effect: deny
    unless:
      - role: data_processor
      - consent: explicit
  - action: external_api_call
    effect: allow
    require:
      - trust_rating: ">= 600"

Shared Evaluation Engine

Same policies, three enforcement points. Shift-left at CI/CD. Pre-action at the gateway. Post-hoc at the observer.

CI/CD — shift-left validation
Gateway — pre-action enforcement
Observer — post-hoc audit

Trust Recovery

When trust breaks, we diagnose why. Card gaps mean missing documentation — fix the card. Behavior gaps mean actual violations — fix the agent.

Card gap: missing or outdated alignment card
Behavior gap: agent violated declared policy

Predictive Intelligence

Fault line analysis identifies where your agent fleet is likely to fail next. Risk forecasting and auto-generated policy recommendations — before incidents happen.

Fault line analysis
Risk forecasting
Auto-generated recommendations

Cryptographic Proofs

Every verdict is Ed25519-signed, hash-chained, and Merkle-tree included. SP1 zkVM STARK proofs are available for every verdict and sampled by default at 10% — selective to keep cost aligned with risk. Trust Ratings publish on Base L2 for independent verification.

SP1 zkVM STARK proofs (sampled · default 10%)
On-chain Trust Rating registry (Base L2)
Independent verification

How Mnemom compares.

The only platform combining pre-action enforcement, policy DSL, cryptographic proof, and a cross-tenant Mnemom AEGIS Managed Rules pipeline.

FeatureMnemomArizeLangfuseLangSmithPatronusGalileo
Pre-action enforcement
Policy DSL
Predictive intelligence
Cryptographic proof
On-chain Trust Rating (Base L2)
Trust recovery
Cross-tenant AEGIS Managed Rules
Mutation-phase adversarial arena
Public STIX 2.1 IoC feed
Append-only signed audit chain

EU AI Act Article 50 — mapped.

Every transparency obligation, covered. Compliance presets ship in the SDKs.

RequirementCLPI Feature
Transparency documentationAlignment cards + integrity certificates
Audit trailsImmutable hash chains with Merkle proofs
Risk categorizationFive-component Trust Rating with drift detection
Compliance reportingExportable compliance bundles with cryptographic attestation
Real-time monitoringContinuous integrity checks, not quarterly audits

Deadline: August 2, 2026. Compliance presets ship in the SDKs today.

EU AI Act — Articles 10, 12, and Annex IV mapped.

The full enforcement provisions, not just Article 50 transparency. Every governance event is signed and audit-chainable — the regulator's question and Mnemom's answer share a primitive.

ArticleRequirementHow Mnemom answers
Article 10Data governanceAlignment Cards declare data boundaries; AIP back-door screening verifies every output against PII/PHI patterns; CLPI Phase 2 governs the card lifecycle and amendments.
Article 12Record-keepingEvery integrity checkpoint, Managed Rule promotion, and advisory publication is Ed25519-signed and append-only chained. CLPI Phase 4 anchors Trust Ratings on Base L2 for independent verification.
Annex IVTechnical documentationExportable compliance bundles — Alignment Cards, IntegrityCheckpoints, signed promotion envelopes, advisory chains — assembled from the same primitives the runtime uses.

Ready for governance that's more than a dashboard?

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