| What it does | Validate and monitor AI and LLM models for accuracy, robustness, and governance
| Realistic API simulators for training and testing
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| Stage | Not given
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| Founded | Not given
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| Based in | IL
| US
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| Pricing model | Not given
| Freemium
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| Pricing | Not given
| Free: $0 with GitHub, Linear and Slack simulators, 10 free hours per month. Pro: $89.99 per seat per month with full catalog, $100 usage credit per seat, $0.012 per simulator-minute after credit. Enterprise: custom pricing.
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| Key features | - Real-time monitoring and alerts for model mistakes
- Comprehensive validation metrics for stability and accuracy
- Model explainability at global and local levels
- Detection of anomalies and model vulnerabilities
- Bias and fairness analysis
- Governance tools for regulatory compliance
- Automated real-time reporting for stakeholders
- Actionable mitigation steps and risk reduction
- Production monitoring to prevent performance deterioration
- Real-time prediction explanation with error and certainty metrics
| - Slack simulator
- GitHub simulator
- Stripe simulator
- Kalshi simulator
- Verified against live APIs
- Latency and fault injection
- Settable state
- Local and CI execution
- Verified UIs
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| What makes it different | - Outperforms international explainability benchmarks like SHAP and LIME
- Unique ability to dive into local samples in real time
- Patent-pending proprietary methodology
- Comprehensive solution covering development and deployment
- 82% faster time to production
| - Validated against real APIs daily with published accuracy percentages
- Stateful simulators that maintain state across calls
- Local execution with no rate limits
- Supports 20+ API integrations including Stripe, GitHub and Slack
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| Community votes | 0 | 0 |
| DR (Domain Rating by Ahrefs) | 26 ▲ +1 (up) since last check | 2 ● no change since last check |
| Trust Flow (Majestic) | 6 | 13 |
| Citation Flow (Majestic) | 16 | 30 |
| Referring domains (Majestic) | 77 | 41 |