About Deepchecks
Deepchecks offers a library and platform for automated testing and validation of ML models and data, including suites for data integrity, distribution checks, model performance, and LLM/agent evaluation. It supports pre-deployment tests, CI pipelines, and production monitoring for traditional ML and LLM-based applications.
Key Features
- Test suites for data and model validation — pre-built checks for data integrity, distribution shifts and model issues
- LLM evaluation & auto-scoring — tools for configuring auto-scoring and comparing LLM/agent outputs
- CI/CD and monitoring integration — run checks in development pipelines and monitor production
- Research-backed tools and libraries — open-source roots and documented validation workflows
Use Cases & Best For
Data scientists and MLOps teams needing automated pre-deployment checks and CI integration
Teams evaluating LLM-based apps with auto-scoring and version comparisons
About Model Evaluation
Test and evaluate AI models