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What is AgentWarden?

AgentWarden is a comprehensive permission and approval management system designed specifically for AI agents. It provides granular control over what actions your AI agents can perform, with built-in approval workflows for sensitive operations.

Permission Control

Define exactly what your AI agents can and cannot do with fine-grained permissions

Approval Workflows

Require human approval for sensitive or high-risk actions

Complete Audit Trail

Track every action your agents attempt with comprehensive logging

Easy Integration

Simple SDK integration with just a few lines of code

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Why AgentWarden?

As AI agents become more autonomous and powerful, the need for robust permission systems becomes critical. AgentWarden solves key challenges:

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🛡️ Security & Control

Prevent AI agents from performing unauthorized actions. Set limits on transaction amounts, API calls, and data access.

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👁️ Visibility

Know exactly what your AI agents are doing at all times with comprehensive logging and real-time monitoring.

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✅ Compliance

Meet regulatory requirements with approval workflows and complete audit trails for all agent actions.

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🚀 Scale with Confidence

Deploy AI agents in production with the confidence that they can’t go rogue or exceed their intended boundaries.

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How It Works

1

Define Your Agents

Create agents in the AgentWarden dashboard and configure their basic settings.
2

Set Permissions

Define what actions each agent can perform and set limits (e.g., max transaction amounts).
3

Integrate SDK

Add the AgentWarden SDK to your application with just a few lines of code.
4

Check Before Acting

Before your agent performs any action, check with AgentWarden if it’s allowed.
5

Log All Actions

Log every action your agent takes for complete visibility and audit trails.

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Quick Example

Here’s how simple it is to protect your AI agent actions: 
from agentwarden import AgentWarden

# Initialize
guard = AgentWarden(api_key="your-api-key")

# Check permission before acting
result = guard.check(
    agent_id="customer-support-bot",
    action="stripe.refund",
    context={"amount": 50.00}
)

if result.allowed:
    # Safe to proceed
    process_refund(amount=50.00)
    
    # Log the action
    guard.log(
        agent_id="customer-support-bot",
        action="stripe.refund",
        status="success",
        context={"amount": 50.00}
    )
else:
    # Action blocked or requires approval
    print(f"Action blocked: {result.reason}")

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Use Cases

Control which actions your customer support AI can take - process refunds up to $100 automatically, but require human approval for larger amounts.
Ensure AI trading bots or financial assistants stay within risk parameters and regulatory requirements with transaction limits and approval workflows.
Allow AI agents to deploy to staging automatically but require approval for production deployments or infrastructure changes.
Define which databases, APIs, or data sources AI agents can access and log all data retrieval operations.

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Ready to Get Started?

Quickstart Guide

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