AI teams need objective ways to measure AI performance before deployment and as models evolve.
Standardized benchmarks provide useful performance indicators, but they don’t always reflect the complexity of real-world use cases, specialized domains, or global user expectations.
DATAmundi designs and executes custom AI benchmarking programs for frontier AI models. We combine expert human evaluation, side-by-side model comparisons, and robust scoring frameworks to measure model performance across languages, cultures, domains, and real-world use cases.
Design and execute benchmarking programs aligned with model capabilities, target users, and business objectives. Develop representative test datasets, evaluation criteria, and scoring frameworks to measure accuracy, reliability, factuality, safety, and task effectiveness.
Evaluate competing models, model versions, and configurations against consistent test scenarios and scoring criteria. Identify relative strengths, weaknesses, and performance differences to support informed model selection and development decisions.
Test model performance across languages, dialects, cultures, and regional contexts. Our DATAtalent global contributor network enables culturally relevant evaluations that reveal performance gaps overlooked by English-centric benchmarks.
Combine structured human assessment, rubric-based scoring, and domain-specialist review to evaluate complex model outputs. Apply expert judgment to assess reasoning, factual accuracy, contextual relevance, and other qualities that automated metrics may miss.
Translation
Localization
Multilingual Content
Quality Assurance
01
Expert-Defined Evaluation Frameworks
Develop task-specific scoring rubrics, assessment guidelines, and performance criteria tailored to intended applications.
02
Global Human Intelligence.
DATAtalent global multilingual contributors and domain specialists support evaluation in 200+ languages.
03
Continuous Performance Tracking
Repeat benchmarking throughout model development and deployment to measure improvements, identify regressions, and monitor performance as models evolve.
Experienced linguists and specialists bring language and cultural context to every project.
Support across languages, markets, and cultural environments.
Flexible workflows, CAT tools, CMS/TMS integrations, APIs, and AI-assisted translation.
Multi-stage linguistic review and QA help maintain accuracy and consistency.
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