Customer-authored policies
Match agent, action, and resource patterns, then apply deterministic conditions and priorities.
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AI Agent Guardrails
Guardrails for autonomous AI agents.
AI Agent Guardrails decide what your AI agents are allowed to do — allow, deny, or challenge every action in real time, with post-quantum-signed proof.
Built for security teams managing Autonomous AI Agents across large organizations.
Allow
Deny
Challenge
The problem
Agents can act. Hope is not an authorization model.
AI Agent Guardrails are safety and policy controls that intercept an agent's execution loop to ensure its actions remain predictable, secure, and compliant.
Autonomous AI agents can access data, use credentials, call tools, and take consequential actions. Most teams can only hope they behave. AI Agent Guardrails put an enforceable decision in front of every action.
How it works
The enforcement loop.
The AI interprets and orchestrates, but a deterministic policy engine makes every ALLOW, DENY, or CHALLENGE decision. If AI Agent Guardrails cannot be reached, the SDK fails closed by default.
- 01
Request an action
Your agent identifies itself and submits the action, resource, and relevant context.
- 02
Evaluate policies
AKRUM’s deterministic engine matches your policies, conditions, identity, and optional prebuilt guardrails.
- 03
Return a decision
AI Agent Guardrails return allow, deny, or challenge, with a reason and any required obligations.
- 04
Enforce before execution
The drop-in SDK runs the tool only on allow. Unreachable checks fail closed by default.
Capabilities
Control the action, not the conversation.
Registered identities
Authorize known agent handles and optionally pin API keys to a single identity.
Obligations and challenges
Require human approval, step-up checks, or other explicit obligations before an action proceeds.
Deterministic and explainable
Every outcome follows declared precedence and returns the matched policy, reason, and obligations.
Drop-in enforcement SDK
Gate tools with authorize, enforce, or wrapTool from a dependency-free TypeScript client.
Domain packs
Prebuilt guardrails for specialized decisions.
Optional, prebuilt guardrails you can attach — AI Agent Guardrails work with your own policies alone, or are supercharged with these.
Crypto Compliance
OFAC, EU, and UK sanctions screening with FATF Travel Rule checks.
ExploreHealthcare Compliance
Deterministic HIPAA and HITECH control evaluation.
ExploreRisk Prediction
Rule-based risk scoring for sensitive agent actions.
ExploreEncryption Optimization
Workload-aware encryption recommendations as a policy input.
ExploreBlockchain Key Manager
Key lifecycle and rotation checks for on-chain operations.
ExploreSigned proof
Every decision comes with verifiable proof.
Every authorization decision is signed with ML-DSA, the FIPS 204 post-quantum signature standard, and written to an exportable, tamper-evident log. An auditor can verify the stored payload offline with AKRUM’s public key.
Read the verification guidedecision.attestation valid
- schema
- guard.decision.v1
- decision
- allow
- suite
- mldsa65-v1
- sha256
- 64e7…9a2c
- verify
- ml_dsa65.verify(signature, payload, publicKey)
Stored payload verified verbatim
Enforce in code
One decision before every tool call.
Call the authorization API directly or use the dependency-free Guard SDK. Both enforce the same deterministic decision contract.
- Bearer key with the guard scope
- Registered agent identity
- Fail-closed SDK behavior
import { createGuardClient } from "./akrum-guard"; const guard = createGuardClient({ apiKey: process.env.AKRUM_API_KEY, onUnreachable: "deny",}); const decision = await guard.enforce({ agent: "payments-agent", action: "create_payout", resource: "account:acct_123", context: { amount: 12500, currency: "USD" },}); // Your action runs only when Guard returns "allow".