Deepchecks is your go-to solution for **evaluating and monitoring LLM-based applications** with ease. Whether you're dealing with complex AI interactions or ensuring compliance, Deepchecks simplifies the process, helping you release high-quality apps without the usual headaches.

What are the features of DeepChecks?

* **LLM Evaluation**: Automate the evaluation of generative AI outputs, saving time and effort. * **ML Monitoring**: Continuously validate your models and data to keep your application running smoothly. * **Open-Source Testing**: Built on a robust, widely-tested Python package used by over 1000 companies. * **Golden Set Automation**: Generate estimated annotations quickly, reducing manual labor.

What are the use cases of DeepChecks?

* **RAG Generation**: Perfect for applications that rely on retrieval-augmented generation. * **Summarization Testing**: Ensure your summarization models are accurate and reliable. * **Compliance Monitoring**: Detect and mitigate issues like hallucinations, bias, and harmful content.

How to use DeepChecks?

1. **Define Your Golden Set**: Start with a set of examples to evaluate your LLM outputs. 2. **Automate Evaluations**: Use Deepchecks to generate estimated annotations. 3. **Monitor Continuously**: Keep an eye on your model’s performance and data quality. 4. **Override When Necessary**: Manually adjust annotations only when needed.