| What it does | Independent auditing for AI agents
| The easiest way to build evals and custom benchmarks for real-world agentic tasks
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| Stage | Not given
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| Founded | Not given
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| Based in | US
| US
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| Pricing model | Freemium
| Freemium
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| Pricing | Startup: 2 audits/reports per month, up to 3 agents. Growth: 4 audits/reports per month, up to 3 agents. Enterprise: 8 audits/reports per month, up to 3 agents. Agentic Enterprise: custom quote, 4+ agents. Free open-source: 60 inspections, self-hosted.
| Free: 100 plan runs per month, $0/month. Pro: 300 plan runs per month, $20/month ($0.067 per run). Ultra: 1,000 plan runs per month, $60/month ($0.06 per run). Top-ups available: 25 runs for $5, 100 runs for $15, 300 runs for $40, 1,000 runs for $120.
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| Key features | - Multidimensional audit covering AI red teaming, operational assurance, philosophical, ethical and sociological dimensions
- Tests for prompt injection, policy violation, tool invocation governance, and authorization
- Assesses epistemic integrity, reality grounding, and frankness
- Evaluates fairness governance and vulnerable user care
- Analyzes stakeholder conflict, influence and systemic risk
- Connect through GitHub or MCP with no manual setup required
- Generates audit reports with evidence and proof of agent behavior
- Open-source engine available for self-hosting
- Detects information hiding, unauthorized decision override, and unauthorized actions
| - Compare treatments (toolsets including skills, MCP servers, CLIs, SDKs)
- Build and version private benchmarks in plain language
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| What makes it different | - Truly independent auditing through outside panel judgment, never internal self-inspection
- Off-the-shelf integration with no manual eval harness or SDK embedding required
- Covers five dimensions of trust: purpose, authority, workflows, responsibility and evidence
- Measures beyond performance to identify misalignment across red teaming, operational, philosophical, ethical and sociological categories
| - Full trajectory visibility showing every step agents took, where they got stuck, and detailed friction analysis
- Compare multiple agents, models, and toolsets simultaneously on identical tasks with one experiment grid
- Managed cloud infrastructure handling durable workflows while you control your own model costs
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 13 ▲ +1 (up) since last check | 13 ● no change since last check |
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| Trust Flow (Majestic) | 11 | 7 |
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| Citation Flow (Majestic) | 31 | 28 |
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| Referring domains (Majestic) | 156 | 130 |
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