Execution control layer for AI agents performing consequential actions
iFixAi
Independent auditing platform for AI agents that checks behavior beyond performance metrics
About iFixAi
iFixAi provides an independent audit of AI agents by evaluating more than 64 categories of potential misalignment. It examines purpose, authority, workflows, responsibility, and evidence to ensure agents operate within approved boundaries. The tool uses a simulation environment to test agents against policies and real-world scenarios without embedding code or building manual eval harnesses. Audits generate detailed reports that reveal hidden actions such as overriding decisions, unauthorized changes, or concealing information, even when standard evaluations show no issues. The process involves connecting an agent via GitHub or MCP, simulating its behavior, conducting the audit, and producing a report with findings. iFixAi is designed for enterprise users and agent developers who require verifiable trust in agent operations.
Key features
- Connects via GitHub or MCP without embedding code
- Simulates agent behavior in a controlled environment
- Audits for policy violations, unauthorized actions, and hidden information
- Generates detailed audit reports with evidence and findings
- Supports self-hosting with open-source engine
- Evaluates purpose, authority, workflows, responsibility, and evidence
- Provides audit badges for verified agents
- Offers multiple pricing tiers for different use cases
Use cases
- Verifying customer support agents before deployment to prevent fraud or unauthorized actions
- Auditing financial agents to ensure compliance with approval workflows and spending limits
- Testing agents handling sensitive data to confirm they do not expose confidential information
Pros
- Evaluates over 64 categories of AI misalignment beyond performance metrics
- Uses simulation environments without requiring code embedding or SDK integration
- Provides independent audits judged by external panels rather than internal teams
- Supports integration via GitHub or MCP with minimal setup required
- Offers self-hosted open-source version for community use
Cons
- No free tier for commercial use beyond the open-source version
- Limited to auditing AI agents and does not cover other AI systems
- Requires connection to agent code or prompts, which may raise privacy concerns
- Pricing tiers are based on number of agents and inspections per month
Frequently asked questions about iFixAi
What does iFixAi do?
iFixAi independently audits AI agents by evaluating over 64 categories of potential misalignment, including purpose, authority, workflows, responsibility, and evidence. It tests agents against policies and real-world scenarios to identify hidden actions such as overriding decisions or concealing information, even when standard evaluations show no issues.
Who should use iFixAi?
iFixAi is designed for enterprise users and agent developers who require verifiable trust in AI agent operations. It suits teams needing to ensure their agents operate within approved boundaries and comply with organizational policies.
How does iFixAi work?
The process involves connecting an agent via GitHub or MCP, simulating its behavior, conducting the audit, and producing a detailed report with findings. The tool uses a simulation environment to test agents without embedding code or building manual evaluation harnesses.
What integrations does iFixAi support?
iFixAi supports integration via GitHub or MCP, allowing teams to connect their agents directly without additional setup. Repositories with an AGENTS.md file are automatically detected and ready for connection.
What does an iFixAi audit report include?
An iFixAi audit report reveals hidden actions such as overriding decisions, unauthorized changes, or concealing information, even when standard evaluations show no issues. It provides detailed findings and proof of an agent's behavior for review.
How can I get started with iFixAi?
To get started, connect your agent via GitHub or MCP, then run the audit through iFixAi's platform. The tool guides users through the process, and no manual evaluation harness or SDK embedding is required.