| What it does | Managed AI trainers, LLM evaluators and benchmark authors for AI labs and data partners
| Validate and monitor AI and LLM models for accuracy, robustness, and governance
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| Stage | Not given
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| Founded | Not given
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| Based in | IN
| IL
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| Pricing model | Contact for pricing
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| Pricing | Not given
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| Key features | - Coding-agent benchmarks in Terminal-Bench and SWE-bench style
- Research reproduction in PaperBench style
- Model evaluation and RLHF with preference ranking
- Long-horizon agent tasks with planning and tool use
- STEM and expert reasoning questions at PhD level
- Trial task scoring before work begins
- Peer review on every item
- Senior reviewer calibration on each batch
- Product design and full-stack development for SaaS and AI
- LLM assistants and voice AI integration
| - 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
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| What makes it different | - One programme lead and point of contact instead of managing hundreds of individual profiles
- Scored trial on your rubric for every expert, not just CV and quiz screens
- Second review on every item plus senior calibration, not just spot checks
- Published quality numbers: 2,500+ tasks authored, 90% acceptance rate, 4.89/5 rating
- Pilot staffing in days with 5 to 10 experts
| - 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
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | Not checked yet ● no change since last check | 25 ● no change since last check |
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| Trust Flow (Majestic) | 0 | 6 |
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| Citation Flow (Majestic) | 0 | 16 |
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| Referring domains (Majestic) | 1 | 77 |
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FynoLabs
Citrusˣ