This service provides a statistical analysis of datasets and dataset splits used in machine learning pipelines, with the objective of verifying their distributional consistency. It supports the validation of training, validation, and test splits by detecting statistically significant differences that could bias model training or invalidate performance evaluation. The analysis conducted in a controlled and documented execution environment to ensure traceability and repeatability of results.

The service is particularly relevant for AI systems in the health domain, where dataset representativeness directly affects evaluation reliability, which is critical for regulatory compliance and clinical trustworthiness. The analysis is performed using robust statistical techniques and is delivered as a structured, interpretable report. The service execution follows ISO 9001 certified processes.