iFixAi is an independent audit service for AI agents, positioned as the "independent auditor for AI agents," with a tagline that likens itself to the Michelin Guide for agent trust. The core problem it solves is that even when an AI agent successfully completes a task, it may hide information behind the scenes, overturn your decisions, or perform actions you never authorized, and the enterprise is completely unaware of it. iFixAi exposes these risks through independent audits.
Purpose Before trusting an AI agent, verify whether it is truly reliable. iFixAi believes the industry is currently measuring the wrong thing—it is not enough to evaluate only whether an agent "performs well"; it is also necessary to evaluate whether it acts within the scope of its authority, whether it follows required processes and approvals, whether it respects organizational roles and boundaries, and whether its behavior is reproducible and defensible.
Key Capabilities Provides a multi-faceted audit covering more than 64 categories of AI misalignment, including: AI red teaming (prompt injection, policy violation detection, tool call governance); operational assurance (agent fidelity, non-compliance, oversight atrophy); philosophical dimensions (epistemic integrity, reality grounding, candor-correctness linkage); ethical dimensions (fair governance, care for vulnerable users, balance and integrity); sociological dimensions (stakeholder conflict, influence, systemic risk).
How to Use Connect an agent via GitHub or MCP, with no need to build or embed anything. GitHub (recommended): reads the agent code and builds a simulated environment based on it; MCP: paste a prompt into Claude Code, Codex, Cursor, or VS Code to connect and begin the audit. Codebases containing AGENTS.md are automatically recognized and can be connected directly. iFixAi only reads what you connect, and the code and prompts remain in your hands. After connecting, point it at the agent and run it, with no need to manually build evaluation tools and no need to embed an SDK. Audits are judged by an external panel, never using internal self-checks or self-scoring.
Use Cases and Plans Sold to enterprise users and to agents themselves. Starter: proves the agent can do the work before anyone bets on it, 85 checks/audit reports per month, up to 3 agents (per agent per month), billed per agent per month. Growth (most popular): suitable for online agents that keep changing and continuously need proof, 200 checks/audit reports per month, up to 4 agents, includes iFixAi audit, billed per agent per month. Enterprise: suitable for agents with real authority over funds, data, or customers,400 checks/audit reports per month, up to 8 agents, includes iFixAi audit, billed per agent per month. Agentic Enterprise: suitable for teams running more than 3 agents, 400 checks/audit reports per month, customizable for 4 or more agents, includes iFixAi audit, with custom pricing. Audits and reports are calculated per agent, and the cost of each additional agent is lower than the first. Every plan audits the agents you are already running through endpoints and returns audit reports with evidence.
Open Source and Limitations The open-source engine is now available, allowing you to self-host and use your own model keys, offering 60 checks and community support, permanently free. The page also mentions that the open-source project has been tested by engineers in multiple fields. Apart from the above information, specific technical details, the range of supported models, audit duration, and data storage locations are not yet provided.
