98% Accuracy | KnoDL
Turn fractured data into clean knowledge — in real time
What it does
Your data is 95% noise. Duplicates, conflicts, fragmented records — and nobody can explain how it got that way. KnoDL is a graph-native reasoning engine that cleans, deduplicates and connects data in real time: 91–98% accuracy, <120ms, no GPU, full explainability. Drop it into your stack via API and finally trust your data.
Does the same job
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We've open-sourced Klarity - a tool for analyzing uncertainty and decision-making in LLM token generation. It provides structured insights into how models choose tokens and where they show uncertainty. What Klarity does: - Real-time analysis of model uncertainty during generation - Dual analysis combining log probabilities and semantic understanding - Structured JSON output with actionable insights - Fully self-hostable with customizable analysis models The tool works by analyzing each step of text generation and returns a structured JSON: - uncertainty_points: array of {step, entropy,…
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Hi HN! I’m Farah, co-founder of Dioptra.ai. We just open sourced katiML (https://github.com/dioptra-ai/katiml) this week and wanted to get your take. katiML is a vector+data lake to debug, curate and version AI data. With katiML, teams avoid the “garbage in, garbage out” effect by taking control over the quality of their data. They quickly and effectively curate high quality data for training, fine-tuning, and fixing hallucinations and edge cases. Features include: - Data Curation: interactive embedding visualization and similarity search, mislabeling and hallucination…
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AstraPixels▲267A pixel-art solar system at its real current positions.
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