Evidently provides both offline evaluations and live monitoring for ML and LLM systems across tabular and text data. It includes 100+ built-in metrics for tasks ranging from data drift detection to LLM evaluation using judge models. Users can start with preset reports or create custom metrics via Python to integrate with existing MLOps and LLMOps workflows.