| What it does | Validate and monitor AI and LLM models for accuracy, robustness, and governance
| Encoding Human Expertise into Machines
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| Stage | Not given
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| Founded | Not given
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| Based in | IL
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| Pricing model | Not given
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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
| - Converse-STT Benchmark for speech-to-text evaluation
- Converse-Diarization Benchmark for speaker attribution
- Expert network with domain specialists
- Audiovisual conversational datasets
- Multilingual conversational AI datasets
- Open-source model post-training research
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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
| - Real-world conversational data from elite professionals
- Multimodal and multilingual expertise encoding
- Rigorous benchmarking with open-source evaluation tools
- Custom data pipelines for each discipline and accent
- Focus on nuance beyond scale, capturing lived experience
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| Community votes | 0 | 1 |
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| DR (Domain Rating by Ahrefs) | 25 ● no change since last check | 27 ● no change since last check |
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| Trust Flow (Majestic) | 6 | 4 |
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| Citation Flow (Majestic) | 16 | 32 |
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| Referring domains (Majestic) | 77 | 264 |
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Citrusˣ
Ocular AI