AI Agent Governance

Rules Engine for AI Coding Assistants & Autonomous Agents

MGE provides mathematical governance for AI agents, ensuring generated code and autonomous actions meet security, performance, and architectural requirements. Every decision is cryptographically verified.

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The Challenge: Ungoverned AI Agents

AI coding assistants and autonomous agents can generate code, modify systems, and execute actions that impact critical infrastructure. Without governance, these actions may introduce vulnerabilities, performance issues, or system instability.

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Code Generation Validation

AI coding assistants generate code that must meet security, performance, and architectural standards before execution.

Challenge:

Generated code may contain vulnerabilities, performance issues, or architectural violations.

MGE Solution:

MGE evaluates generated code against mathematical invariants for security, correctness, and compliance.

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Autonomous Agent Actions

AI agents perform actions like file modifications, API calls, and system changes that require governance.

Challenge:

Agent actions could compromise system integrity, data security, or business logic.

MGE Solution:

Every agent action is validated against governance rules with cryptographic receipts for audit trails.

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Multi-Agent Coordination

Multiple AI agents collaborate on complex tasks requiring coordinated decision-making.

Challenge:

Conflicting actions or race conditions between agents could cause system instability.

MGE Solution:

MGE provides deterministic conflict resolution and ensures coordinated actions meet mathematical consistency requirements.

Mathematical Governance Rules

MGE evaluates AI agent actions against formal mathematical invariants, ensuring deterministic and provable governance.

Code Security Invariants

Generated code must satisfy security properties (no injection vulnerabilities, proper input validation)

∀c ∈ Code: Secure(c) ∧ Validate(c)

Performance Bounds

Code execution must meet performance requirements (time/space complexity constraints)

∀c ∈ Code: Perf(c) ≤ Threshold ∧ Complexity(c) ∈ Bounds

Architectural Consistency

Code must conform to system architecture and design patterns

∀c ∈ Code: Architecture(c) ⊨ SystemDesign

Agent Action Authorization

Agent actions must be authorized based on role, context, and system state

∀a ∈ Actions: Authorize(a, Role, Context, State)

How MGE Governs AI Agents

The complete governance workflow for AI agent actions.

Agent Action Capture

MGE integrates with AI agent frameworks to capture proposed actions before execution.

Rule Evaluation

Each action is evaluated against the complete set of mathematical governance rules.

Decision Rendering

MGE produces a deterministic decision (approve/deny) with reasoning and rule references.

Receipt Generation

Approved decisions receive cryptographically signed receipts for tamper-proof audit trails.

Action Execution

Approved actions proceed to execution; denied actions are blocked with detailed reasoning.

Integration Examples

How MGE integrates with popular AI agent frameworks and coding assistants.

GitHub Copilot Integration

When Copilot suggests code, MGE validates the generated code against security invariants and architectural rules before the developer can accept or modify it.

// Generated code validation const decision = await mge.checkCompliance({ action: 'code_generation', code: generatedCode, context: { language: 'javascript', framework: 'react' } });

Autonomous DevOps Agent

DevOps agents that automatically deploy infrastructure changes are governed by MGE to ensure compliance with enterprise security policies.

// Infrastructure deployment validation const decision = await mge.checkCompliance({ action: 'infrastructure_deployment', changes: deploymentPlan, context: { environment: 'production', region: 'us-east-1' } });

Benefits for AI Agent Governance

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Security Assurance

Mathematical guarantees that generated code and agent actions meet security requirements.

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Deterministic Decisions

Same inputs always produce the same governance decisions, ensuring predictability.

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Complete Audit Trails

Cryptographic receipts provide tamper-proof records of all governance decisions.

Ready to Govern Your AI Agents?

Implement mathematical governance for your AI coding assistants and autonomous agents. Ensure every action meets your security and compliance requirements.

Contact for AI Agent Governance ← Back to MGE Overview