| What it does | An approval layer for unattended AI agents that halts risky actions for human approval before execution
| AI execution infrastructure that turns mission-critical manual tasks into reliable, paid AI services
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| Stage | Not given
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| Founded | Not given
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| Based in | Not given
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| Pricing model | Freemium
| Contact for pricing
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| Pricing | Self-hosted: Free (MIT licensed). Hosted Indie: $49/mo (2 seats, monthly governed-action ceiling, 30-day retention, email support). Hosted Team: $199/mo (10 seats, higher governed-action ceiling, 90-day retention, org-scoped rate limits, priority support).
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| Key features | - Intercepts risky agent actions before execution
- Works with Claude Code, Codex, Hermes, OpenClaw, and MCP
- Policy-based risk scoring and decision making
- Remote approvals from phone or browser
- Signed audit ledger with replayable records
- Calibrated interruptions that reduce false positives
- Enforcement liveness monitoring via synthetic probes
- Self-hosted (MIT licensed) or managed hosting options
- Approvals inbox with decision ledger and policies
- Agent defense documentation with assumptions and shields
| - Job of Work Mapper: identifies valuable processes and maps required outcomes, steps, systems and stakeholders
- Execution Engine: manages multi-week or multi-month workflows with fault tolerance, checkpoints and error recovery
- Built-in stakeholder management: communicates with stakeholders across channels and escalates exceptions
- Intelligence flywheel: captures execution data to benchmark models, improve accuracy and optimise costs
- Small focused AI models in deterministic graph: reduces errors and cost vs single large models
- Fully auditable and explainable execution
- Durable execution engine with checkpoints and automated recovery
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| What makes it different | - Only approval layer that protects unattended runs that walk away
- Signed ledger with replayable audit records and explicit signature verification
- Self-hosted with no infrastructure lock-in or vendor dependency
- Learns from your approvals to reduce interruptions automatically
- Honest about enforcement boundaries across different integrations
| - Handles multi-stakeholder workflows spanning days, weeks or months without requiring core product rebuild
- Partners keep control of brand and customer relationships while using platform for execution
- Usage-based pricing aligns fees with completed outcomes rather than features
- Small focused AI models designed for accuracy and repeatability in high-trust workflows
- Includes mapping stage to validate commercial viability before significant investment
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 7 ▼ −1 (down) since last check | 12 ● no change since last check |
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| Trust Flow (Majestic) | 3 | 8 |
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| Citation Flow (Majestic) | 30 | 29 |
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| Referring domains (Majestic) | 88 | 64 |
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DashClaw
Aguru