The guardian agent for AI’s highest-stakes decisions.
A panel of frontier models argue over your AI agent’s riskiest decisions before they execute.
Plausible enough to ship. Wrong often enough to hurt.
Agent deleted a live production database, then invented ~4,000 fake records to hide it.
“Fixed” a problem by wiping an environment: a 13-hour AWS outage.
Deleted 28,745 lines, took a service down, then wrote a fake post-mortem.
A mistake caught in production costs 30× or more than one caught at decision time.
The best ideas
survive the argument.
Courts make two sides argue. Science invites refutation. One AI checking itself shares its own blind spots, so we make four rivals argue instead.
Cross-examination, not polling. The findings live between the models.
Unskippable when stakes are high. Invisible when they are not.
Plus any MCP client. The panel follows the developer, not one vendor’s tool.
Only what the agent passes leaves the machine — never your repository, file tree, or codebase. Risk classification runs 100% locally.
We never train models on your code. Bring your own provider keys or cloud account for provider-side certainty.
The client is open source — MIT-licensed, zero runtime dependencies. Read every line before you trust it.
Including a security hole caught one commit from production.
Under a minute to armed gates · 50 free credits · fully undoable