Why LILT for model evaluation
Applied AI research partner
LILT brings research-grade expertise and real-world experience evaluating multilingual AI systems across languages, domains, and modalities.
Governed human judgment (not crowdsourced)
A long-lived, curated evaluator network with multi-stage qualification, continuous verification, and longitudinal performance tracking.
Comparable signals at global scale
Calibration, anchors, and agreement tracking turn human evaluation into a consistent measurement instrument across 300 locales.
Overview
Model evaluation breaks down when signals shift across languages, cultures, and rater populations.
LILT operationalizes human judgment as a continuous system—so teams can compare models reliably, detect regressions early, and ship globally with confidence.
What you can do with LILT
Run multilingual model evaluation and+ diagnostics that stays consistent across regions and time.
Use disagreement and ambiguity as a diagnostic signal to surface hidden failure modes.
Detect drift, bias, and rubric reinterpretation in-pipeline—before it hits production challenges
Identify language- and culture-specific failure modes that monolingual testing misses.
Pevent rater drift, variance, or instability over time.
How LILT delivers
Co-design evaluation frameworks with your model team (rubrics, anchors, gold sets).
Continuous calibration, + readiness scoring, + outlier and drift detection.
Integrates into existing model pipelines as the evaluation/readiness layer (no platform replacement).
