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iFixAi

iFixAi independently audits AI agents for unauthorized actions, policy violations, approval bypasses, and operational risks, with replayable proof via GitHub or MCP.

iFixAi

Independent auditing for AI agents

iFixAi is an independent auditing service for AI agents. It is designed to assess whether an agent can perform its assigned job without exposing information, exceeding its authority, bypassing approvals, misleading users, or taking actions that were not authorized.

Rather than measuring general capability alone, iFixAi examines purpose, authority, workflows, responsibility, and evidence. Its process connects to an existing agent, simulates scenarios, runs adversarial and operational checks, and returns an audit report with proof that can be reviewed and replayed. The site says the service covers more than 64 categories of possible AI misalignment.

Key features

Multidimensional agent auditing

Tests whether an agent stays within permissions, follows required approvals, respects organizational roles, and can be held accountable for its behavior.

Adversarial and assurance checks

The audit categories include prompt injection, policy violations, tool invocation governance, principal fidelity, oversight atrophy, epistemic integrity, fairness governance, vulnerable-user care, stakeholder conflict, influence, and systemic risk.

GitHub and MCP connection workflow

Connect an existing agent through GitHub or MCP without first building an evaluation harness or embedding an SDK. GitHub connections are used to build a simulation environment from the agent code.

Simulation-to-report workflow

The illustrated workflow runs through connect, simulate, audit, report, and badge, separating the test process from the agent's normal success metrics.

Replayable evidence

Audit reports include proof intended to make findings replayable and defensible. The site also presents inspection and report identifiers for audited scenarios.

Independent assessment

The product is positioned as an outside assessment rather than internal self-inspection or self-scoring, and is offered for agents already running over an endpoint.

Use cases

  • Pre-deployment agent review

    Run an independent check before deploying an agent that can handle refunds, account changes, customer communications, or other operational actions. The audit is intended to expose unauthorized behavior that ordinary success metrics may miss.

  • Ongoing assurance for changing agents

    Assess a live agent as its prompts, tools, policies, or surrounding workflows change, using reports to identify whether the new behavior remains within its intended authority.

  • High-authority business workflows

    Test agents that can affect money, data, or customers for approval bypasses, policy violations, hidden information, and unauthorized tool use before those capabilities create operational risk.

  • Self-hosted inspection

    Use the self-hosted open-source engine with your own model keys when a team wants to run inspections in its own environment rather than start with the hosted packages.

Pros and Cons

Pros

  • Checks agent behavior across authority, approvals, responsibility, ethics, and evidence rather than relying only on task-success benchmarks.
  • Connects to an existing agent through GitHub or MCP without requiring a manually built evaluation harness or embedded SDK first.
  • Produces audit reports with proof and uses a five-stage workflow covering connection, simulation, auditing, reporting, and badging.
  • Includes a free, self-hosted open-source engine with user-supplied model keys.

Cons

  • The collected source does not document supported agent platforms, integrations beyond GitHub and MCP, security controls, or technical requirements in detail.
  • Pricing amounts are not provided in the available pricing content, so plan costs require confirmation from iFixAi.

FAQ

How is an agent connected to iFixAi?

iFixAi connects to an existing agent through GitHub or MCP. With GitHub, it reads the connected agent's code and builds a simulation environment. With MCP, a prompt can be used in Claude Code, Codex, Cursor, or VS Code to connect and start the audit.

What does the iFixAi audit process produce?

The workflow is presented as five stages: connect, simulate, audit, report, and badge. The service returns an audit report with proof for the agent tested over its endpoint.

What does iFixAi evaluate beyond standard benchmarks?

The source describes iFixAi as an independent auditor that checks more than general task performance, including authority, required workflows and approvals, organizational boundaries, and whether behavior can be reproduced and defended.

Does iFixAi offer a free version or paid plans?

A free, self-hosted open-source engine is listed with users supplying their own model keys. The source also lists paid Startup, Growth, Enterprise, and Agentic Enterprise packages, but does not provide prices in the collected content.

Quick Facts

Category
AI developer tool / AI agent auditing
Connection methods
GitHub and MCP
Workflow
Connect, simulate, audit, report, badge
Open-source option
Free self-hosted engine with your own model keys
Paid offerings
Startup, Growth, Enterprise, and Agentic Enterprise plans are listed; prices are not shown
Source domain
ifixai.ai