Agent Intent & Context
An AI Agent or wallet requests an action with actor, action, asset, amount, and operational context. The Execution Gateway intercepts the request before it reaches the target system.
CompliAGL Execution Governance
Govern autonomous actions before they execute. The CompliAGL Hedera demo visualizes the full execution-governance lifecycle: AI Agent request, Execution Gateway interception, CompliAGL evaluation, and a deterministic ALLOW / DENY / REQUIRE_APPROVAL outcome — with proof.
CompliAGL Execution Governance
CompliAGL Execution Governance
OP
Scenario
Normal ActionALLOW
Governance Decision
PendingPending
Core Action Executions
0Pending
Gateway State
ReadyPending
Step 1
Scenario Configuration
Select a live demo scenario and run the governed action
Step 2
Governance Decision
Pre-execution policy evaluation and reason codes
Select a scenario and run the governed action to see the decision.
Step 3
Execution Outcome
Gateway enforcement and execution count
Run the governed action to see the execution outcome.
Step 4
AIProof / Governance Evidence
Machine-verifiable evidence for the governed action
Run the governed action to see the AIProof or governance evidence.
Frameworks & Standards
Governance framework operationalization
Operationalize governance across frameworks, controls, and execution from one platform.
Execution Governance
The demo exercises a single, focused execution-governance path: from agent request through interception, evaluation, and enforcement — producing an auditable proof of whether the action ran or was stopped.
Pre-Execution Governance
CompliAGL evaluates the action against deterministic policy and returns one canonical decision: ALLOW, DENY, or REQUIRE_APPROVAL. Every decision is recorded before execution proceeds.
The Problem
Autonomous execution needs governance before it needs execution
- Autonomous actions move faster than governance
- AI agents, wallets, and workflows can initiate transfers, borrows, and operational actions without a human in the loop. A single anomalous oracle or misconfigured limit can expose the organization to irreversible risk before anyone notices.
- Existing controls only observe after the fact
- Monitoring and logging capture what already happened. CompliAGL intercepts the action before execution, evaluates it against deterministic policy, and returns ALLOW, DENY, or REQUIRE_APPROVAL in milliseconds.
- Decisions must be provable, not just logged
- Each governed action generates an AIProof bundle capturing the request, the decision, the gateway state, and the execution result. CompliLedger anchors this proof so the outcome can be independently verified.
Why CompliAGL matters
Intent without governance creates risk. CompliAGL evaluates autonomous actions before execution, determines authorization through deterministic reasoning, and generates AIProof for complete lifecycle transparency.
Platform Principle
Why governance must precede autonomous execution
A live demonstration of pre-execution governance
The CompliAGL Hedera demo is built for screen recording, investor meetings, and ecosystem demos. It proves that an autonomous action can be governed, blocked, or paused before execution — and that the system can prove the outcome.
3
Live demo scenarios exercising ALLOW, DENY, and REQUIRE_APPROVAL — Normal Action, Bonzo-Style Oracle Incident, and Human Approval Required
5
Execution-path nodes from AI Agent through Hedera Agent Kit, CompliAGL Adapter, Execution Gateway, and CompliAGL to final execution or block
0
Core Action Executions in the Bonzo-style DENY scenario — the action is intercepted and blocked before it can execute
turns AIProof into machine-verifiable proof — CompliAGL governs autonomous execution before it happens, CompliLedger proves the outcome.
The demo produces a clear proof for every outcome. ALLOW runs to execution and records the AIProof bundle. DENY and REQUIRE_APPROVAL record the governance decision evidence and mark execution evidence as not applicable or pending — never implying an action executed when it did not.
Explore the demoPlatform Adoption from policy to proof
Three practical entry points for organizations moving from governance planning to controlled production execution. CompliAGL is AI-native, deterministic, policy-driven, explainable, chain-agnostic, and execution-adapter agnostic.
Governance Foundations
Map policies and frameworks into executable controls.
#1· In Development
executive overview
- Policy-to-control translation
- Framework mapping and control alignment
- Decision traceability
- Governance readiness assessment
- Designed for enterprise operating teams
Governed Execution
Most popularControl how machine and enterprise actors execute in production.
#2· In Development
executive overview
- Identity-bound actor governance
- Policy-gated execution workflows
- Operational approvals and controls
- Workflow adapters for real systems
- Runtime enforcement before action
Proof & Assurance
Generate evidence that stands up to audit and verification.
#3· In Development
executive overview
- Canonical Proof Package
- Machine-verifiable evidence
- Structured audit artifacts
- Independent verification workflows
- Cross-stakeholder trust and portability
Need a governance operating model for AI?
We work with teams that need a practical path from policy and framework obligations to governed execution and portable proof in production.
Frequently asked questions
Common questions from enterprise teams evaluating execution governance, operational control, and proof for AI systems in production.
CompliAGL is the AI Execution Governance Platform that governs autonomous AI execution through policy automation, deterministic decision-making, and machine-verifiable proof. Powered by CompliLedger Proof Infrastructure.
See autonomous execution governed in real time
Run the CompliAGL Execution Governance demo and watch an AI Agent request move through the Hedera Agent Kit, CompliAGL Adapter, Execution Gateway, and CompliAGL — with a verifiable AIProof of the outcome.