| What it does | Physics-based AI that optimizes complex industrial systems in real time
| AI debugging for modern engineering teams
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| Stage | Not given
| Startup
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| Founded | Not given
| 2025
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| Based in | US
| US
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| Pricing model | Contact for pricing
| Freemium
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| Pricing | Not given
| 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.
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| Key features | - Physics-native optimization grounded in system physics
- Multi-fidelity data fusion with real-time feeds
- Guard railed autonomy with rigorous framework
- Decision-making under uncertainty with calibrated confidence measures
- Systems of surrogates for industrial-scale complex systems
- Auditable workflows with complete chain of evidence
- Cloud-native with on-premises support
- REST API and OPC UA integration
- SOC 2 Type II certified security
- Deploys in weeks across entire operations
| - 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
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| What makes it different | - Deploys in weeks, not years or months
- Physics-grounded reasoning beyond historical data patterns
- Measurable outcomes from day one with $100M+ proven results
- Uncertainty-aware recommendations operators can trust
- Operates on mission-critical systems trusted by world's largest energy companies
| - 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
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| Community votes | 1 | 0 |
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| DR (Domain Rating by Ahrefs) | 30 ● no change since last check | 36 ● no change since last check |
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| Trust Flow (Majestic) | 18 | 0 |
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| Citation Flow (Majestic) | 30 | 13 |
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| Referring domains (Majestic) | 141 | 73 |
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Geminus
FixBugs