| What it does | AI debugging for modern engineering teams
| The control layer for AI
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| Stage | Startup
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| Founded | 2025
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| Based in | US
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| Pricing model | Freemium
| Freemium
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| Pricing | Free Trial: 3 bug fixes per month. Pro: $33/month for 15 bug fixes per month (or $24.75/month billed as $297/year with annual discount). Super User: $60/month for 30 bug fixes per month (or $45/month billed as $540/year with annual discount). Enterprise: Custom pricing with custom bug fix volume.
| Free plan: €0/month with 10,000 proofs included per month. Starter: €59/month with 50,000 proofs, then €0.0015 per proof above. Growth: €249/month with 500,000 proofs, then €0.0005 per proof, then €0.0002 after 2,000,000 proofs. Enterprise: from €990/month or €15,000/year licence with 5,000,000 proo
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| Key features | - Automated alert triage from monitoring stack
- Root cause analysis across distributed systems
- Issue reproduction in controlled environment
- Validated fix generation with test cases
- VS Code extension for local debugging
- GitHub App for automated analysis
- Self-hosted deployment option
- Integration with logs, traces, metrics and alerts
- Visible reasoning chain for every fix
- Triage sessions shareable and reloadable
| - Wraps AI provider clients with policy enforcement before calls execute
- Enforces provider-level privacy parameters like store=false for OpenAI
- Generates signed, non-reusable ACT tokens for each request
- Maintains append-only, hash-chained ledger for audit verification
- Embedded preference widget with cross-app persistence
- Global Privacy Control signal detection and enforcement
- Fails closed when unreachable; no fallback mode
- Python and Node.js SDKs with source-available licence
- Policies defined in dashboard, not in code
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| What makes it different | - Validation-first approach with reproduction tests and regression verification
- Built specifically for debugging existing bugs, not writing new code
- Handles complex distributed systems with stateful, auditable workflows
- No hard upper limit on context, processes automated log and trace ingestion
- Local deployment keeps code on user's machine
| - Cryptographic proof of compliance: signed, verifiable tokens and append-only ledger that auditors can verify without vendor involvement
- Policies live in dashboard, never touch code, preventing unauthorized modifications
- Separates user preference control from developer code, ensuring developer cannot alter consent
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 36 ▼ −1 (down) since last check | Not checked yet ● no change since last check |
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| Trust Flow (Majestic) | 0 | 0 |
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| Citation Flow (Majestic) | 13 | 0 |
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| Referring domains (Majestic) | 73 | 0 |
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FixBugs
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