Vals AI

Vals AI is a comprehensive evaluation platform designed specifically for testing and benchmarking large language model (LLM) applications including copilots, RAG systems, and AI agents. The platform addresses critical gaps in AI evaluation by providing industry-specific benchmarks that reflect real-world use cases rather than academic datasets.

At its core, Vals AI uses Test Suites composed of multiple Tests, each with specific inputs and Checks that evaluate whether model responses meet defined expectations. This structured approach enables systematic evaluation of AI applications across domains like Legal, Finance, Healthcare, Mathematics, and Coding.

The platform offers both private benchmarking capabilities to prevent data leakage and public benchmark resources. Their public benchmarks (available at vals.ai/benchmarks) provide valuable free resources for model comparison across categories like Legal (CaseLaw, ContractLaw, LegalBench), Finance (CorpFin, Finance Agent, TaxEval), Healthcare (MedQA), Math (AIME, MGSM), Academic (GPQA, MMLU Pro), and Coding LiveCodeBench, SWE-bench.

Vals AI integrates seamlessly into development workflows through SDK and CLI tools, enabling automated testing, CI/CD pipeline integration, and regression testing. The platform also supports expert-in-the-loop evaluation with review workflows and annotation capabilities, combining automated metrics with human expertise for comprehensive AI application assessment.

For enterprise teams building AI applications, Vals AI provides the infrastructure needed to ensure model performance, accuracy, and reliability before deployment, with detailed analytics on cost, latency, and quality metrics.