Case Study: Frontier Lab achieves best-in-class multilingual evaluation quality with LILT

Frontier Lab achieves 95% alignment with Lilt

Frontier Lab, a leading AI lab, needed to evaluate its most advanced models across 22 languages. Traditional crowd-based pipelines could not deliver the depth or consistency required for complex tasks like nuanced error analysis and multimodal comprehension. They partnered with LILT to power their multilingual evaluation pipeline.

LILT treated the project as an engineering discipline, implementing a rigorous qualification process with over 2,000 test modules and a calibration-first approach. The solution delivered best-in-class data, ranking first on the program's hardest task. LILT achieved a 95% post-calibration alignment rate, maintained an ejection rate under 3%, and doubled its contributor pool over a single weekend to meet spiking demand while preserving quality.

Frontier Lab