| What it does | Testing and improvement for GenAI systems, before deployment and in production
| Language decoding system that extracts core content and organizes knowledge using semantic energy measurement
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| Stage | Not given
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| Founded | Not given
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| Based in | US
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| Pricing model | Not given
| Freemium
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| Pricing | Not given
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| Key features | - Automated evaluations with off-the-shelf benchmarks and LLM as Judges
- Product strategy and cross-department PM modules
- Automated alerts for deviations in product behavior
- LLM as Users for simulating diverse user personas
- AI portfolio governance and oversight
- User feedback automation and expert annotation
- Metrics comparison with historical data and leaderboards
- Customizable metrics for different knowledge levels and evolving needs
- Integration with existing workflows for cross-departmental teams
| - Runs locally in browser via WebAssembly
- Document-based Q&A and analysis
- Report writing and document drafting
- Multilingual translation
- Cloud-based LLM service
- Hallucination mitigation through semantic filtering
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| What makes it different | - Measures real-world impact to prove business and user value before deployment
- Metrics become shared language across product, engineering and risk teams
- Reduces reliance on data scientists by automating AI product management
- Makes impact of AI predictable through testing and forecasting
- Ensures AI aligns with actual user needs through feedback and explainability
| - Data never leaves the user's device when using local mode
- Separates processing brain from execution interface to reduce hallucinations
- Cloud mode requires no high-end device or complex setup
- Quantifiable extraction metrics (AMP%, DAMP%, compression rates)
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 39 ● no change since last check | 7 ● no change since last check |
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| Trust Flow (Majestic) | 7 | 2 |
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| Citation Flow (Majestic) | 23 | 13 |
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| Referring domains (Majestic) | 84 | 19 |
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Impact AI