Deepchecks
Evaluation, testing and monitoring for LLM applications and ML models
About Deepchecks
Deepchecks provides tools for evaluating and monitoring machine learning models and LLM-based applications, including an open-source testing package. It is aimed at AI teams that need to validate quality before and after deployment.
Common use cases
- LLM application quality testing
- Production model monitoring
- Pre-deployment validation
Products and services
Deepchecks LLM Evaluation
Evaluation and monitoring of LLM applications.
Deepchecks open source
Python package for testing ML models and data.
Key features
- LLM evaluation
- Model monitoring
- Data validation
- Open-source testing
- Production tracing
Deepchecks alternatives
- Arize AIObservability and evaluation platform for AI agents, LLMs and ML models
- FiddlerObservability, evaluation and guardrails for ML models and AI agents
- GalileoEvaluation, observability and guardrails platform for AI agents and LLM apps
- Evidently AIOpen source and cloud tools to evaluate and monitor ML and LLM systems
FAQs
Is there open source?
Yes, an open-source testing package.
What does it evaluate?
LLM apps and ML models.
How is it priced?
Open source plus paid tiers.

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