Frontier Alignment

Multilingual LLMaaJ Managed Service

Turnkey managed service that provides structured, rubric-based evaluations of multilingual model outputs

Fully managed endpoint service for evaluation at scale across locales and use cases. Appen owns the entire LLM judge pipeline end to end, from prompt engineering, model selection, search provider tuning, and rubric optimisation through to ongoing monitoring, all kept in alignment through continual human QA sampling and confidence-based adjudication.

The service follows a two-phase approach: first, calibrating the LLM judge against human-annotated golden sets, then running ongoing quality assurance in production to ensure it stays aligned.

What Appen Delivers

Calibrated LLM Judge

During calibration, an LLM judge is calibrated to your quality standards through iterative prompt engineering, model selection, and parameter tuning against a golden set of human-annotated samples. The process continues until the automated judge achieves the target agreement threshold with human ground truth, establishing a reliable foundation for scaled evaluation.

Ongoing Human QA Sampling

Ongoing weekly QA sampling of LLM Judge in production where stratified evaluation instances are independently scored by human reviewers and compared against LLM judge outputs, detecting drift, emerging biases, and edge cases that automated monitoring alone would miss.

Confidence-Based Human Adjudication

Proprietary confidence scoring that automatically directs low-confidence cases to expert human reviewers for adjudication, ensuring ambiguous or challenging evaluations receive the scrutiny they require.

Hybrid approach combining automated LLM-based evaluation with human review

Appen’s LLMaaJ Managed Service delivers the speed and scalability of automated evaluation with the precision and cultural sensitivity of human expertise. Under this managed service model, expert human review is applied in targeted, high-impact areas and edge cases.

For teams evaluating multilingual and culturally nuanced model outputs, this hybrid approach is what enables reliable evaluation at scale across multiple locales.

Related Resources

White Paper

Multilingual LLM-as-a-Judge Managed Service for Evaluation at Scale

Appen's Multilingual LLMaaJ Managed Service delivers rubric-based LLM evaluation across numerous use cases and languages - combining automated speed with human oversight and cultural precision at scale.

Read white paper

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