[antonap]

Arize is a great tool for observability, and their open source product, Phoenix, offers many great features for LLM evaluation as well.

Some key unique advantages we offer:

- Component-level evaluation, not just observability: Many great tools on the market can help you observe different components (or execution steps) in a GenAI system for each data sample. What we offer on top of that is the ability to do automatic evaluation and have metrics for each step of the pipeline. For example, you will be able to have metrics on the accuracy of agent tool usage, precision / recall for each retriever step, and relevant metrics on each LLM call.

- Leverage user feedback for offline evaluation: We allow you to create custom metrics based on your past user feedback data. Unlike predefined metrics, these custom metrics are trained to learn your specific user preferences. In a sense, these metrics simulate user ratings.

- Synthetic Data Generation: Large amounts of synthetic data can help you stress test your AI system beyond your existing data. They also come in greater granularity than human curated datasets and can help you test and validate.

[esafak]

I always recommend a comparison page. Help prospects decide.

[antonap]

Great suggestion, thanks!