Human-above-the-loop
100 human labels.
The statistical power of 200.
Stop guessing, start measuring
Not "91% accuracy (LLM judge)."
But "82% ± 3%, certified."
What is GLIDE?
GLIDE (Generated Label Inference & Debiasing Engine) is a Python library for rigorous evaluation of GenAI systems.
- LLM judges are biased. Proxy evaluators systematically over- or under-estimate true performance.
- Human annotation is expensive. Full labeling at scale is rarely feasible.
- GLIDE bridges the gap. Thanks to prediction-powered inference, it combines both to produce valid, unbiased performance estimates.
Key features
- Unbiased performance and risk estimates
- Smart annotation budget allocation to minimise human labeling
- Guaranteed confidence intervals regardless of proxy quality
- Works for any metric, any AI system, any unstructured output requiring annotation
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