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AI Agent Governance

Control what your AI agents can do before they act. Aguardic evaluates every tool call, workflow step, and autonomous decision against your safety and compliance policies in real time.

Why Agent Governance Matters

AI agents act autonomously — calling tools, accessing data, and making decisions without human review. Without governance, a single misconfigured agent can:

Agents execute tool calls that delete data, send emails, or modify infrastructure — without human review
Sensitive customer data is accessed or exfiltrated through uncontrolled agent workflows
Autonomous decisions bypass organizational policies and compliance requirements
Multi-step agent chains amplify errors — one bad decision cascades through an entire workflow
No audit trail of what agents did, why, or what data they accessed

Why System Prompts and Wrappers Aren't Enough

System prompts can be bypassed through prompt injection and jailbreaking
Wrapper libraries lack organizational policy awareness and context
No centralized audit trail of agent actions across tools and workflows
Enforcement is inconsistent — different agents, different rules, different outcomes
Static guardrails can't adapt to new tools, APIs, or agent frameworks

Agent governance requires enforceable rules — not suggestions.

How Aguardic Governs AI Agents

Evaluate every agent action before it executes. Define what's allowed, enforce it in real time, and log everything for compliance.

1

Define agent action policies

Write rules for tool call restrictions, data access boundaries, cost thresholds, and approval requirements.

2

Intercept every agent action

Aguardic sits between your agent and its tools, evaluating every tool call and workflow step against your policies.

3

Enforce with block, approve, warn, or monitor

Block unsafe actions, require human approval for risky operations, warn with context, or monitor with a full audit trail.

4

Log everything for compliance

Every agent action is recorded — the tool call, context, policy match, and decision — ready for audit.

Example Rules

Real rules teams enforce on AI agent actions — from tool call restrictions to data access boundaries.

Block agents from executing delete operations on production databases

Safety

Require human approval for file system write operations

Access Control

Flag tool calls that access customer PII or health records

Privacy

Deny agent actions exceeding $1,000 spend threshold per session

Cost

Block unauthorized API calls to external third-party services

Security

Require human-in-the-loop for irreversible actions

Compliance

Prevent agents from modifying infrastructure or deployment configs

Safety

Flag agent workflows that exceed 10 sequential tool calls

Operational

What Happens When an Agent Rule Triggers

Deterministic outcomes your team can rely on. Every violation is handled the same way, every time.

Action is blocked

Unsafe tool calls are denied before execution. Your agent receives a clear error with the policy that triggered.

Escalated for human review

Flagged actions are paused and routed to a human reviewer before the agent can proceed.

Evidence logged for audit

Every evaluation is recorded — tool call, context, matched policy, and decision — for compliance reporting.

Team is alerted

Configurable notifications alert your team to violations via email, Slack, or webhook.

Pre-Built Agent Safety Policy Packs

Start with battle-tested governance rules from the Aguardic Marketplace — then customize for your agents.

Works With Your Agent Stack

Aguardic connects to the platforms where your agents run. Add governance as a middleware layer or use our API and MCP server for custom agent frameworks.

Start Governing AI Agents Today

Connect your agent platforms, apply proven policies, and enforce safety before agents act.