Blog: Arize comparison - added keywords #2624
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| @@ -100,31 +107,61 @@ Arize Phoenix is an open-source LLM observability tool that focuses on providing | |||
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| Arize Phoenix excels in its evaluation capabilities and is well-suited for data scientists and ML engineers working on complex LLM projects. However, it lacks some of the developer-friendly features that Helicone offers, such as self-hosting options, user tracking, and user feedback collection. Arize Phoenix's pricing model may also be less flexible compared to Helicone's tiered approach. | |||
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| ## Why Companies Choose Arize Phoenix Over Helicone? | |||
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| - **Robust Evaluation Capabilities**: Ideal for data scientists focused on model performance. | |||
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but is it the same type of eval as we do?
| ## Why Companies Choose Arize Phoenix Over Helicone? | ||
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| - **Robust Evaluation Capabilities**: Ideal for data scientists focused on model performance. | ||
| - **Integration with ML Workflows**: Seamlessly fits into existing machine learning pipelines. |
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maybe just keep this one
| Both Helicone and Arize Phoenix offer powerful features for LLM observability, but they cater to slightly different audiences. | ||
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| ### Choose Helicone if you: | ||
| * Require self-hosting options for data control and compliance. |
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No, we also have SOC2, the ability to omit storing bodies
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what do you suggest here?
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If they're concerned about control and compliance, Helicone has SOC2, the ability to omit storing bodies and self-hosting options
| Both Helicone and Arize Phoenix offer powerful features for LLM observability, but they cater to slightly different audiences. Helicone's user-friendly approach, comprehensive feature set, and flexible pricing make it an excellent choice for a wide range of users, from solo developers to small and medium-sized teams. Its self-hosting options and advanced features like user tracking and feedback collection give it an edge in many scenarios. | ||
| ### Choose Arize Phoenix if you: | ||
| * Are a data scientist or ML engineer focused on model evaluation. | ||
| * Need advanced tools for assessing LLM performance. |
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No, we have evals too!
| Ultimately, the choice between Helicone and Arize Phoenix depends on your specific needs, team size, and the complexity of your LLM applications. For most users, especially those looking for an all-in-one solution with a gentle learning curve, Helicone appears to be the more versatile and accessible option. | ||
| **For most users**, especially those looking for an all-in-one solution with a gentle learning curve and features like self-hosting, user tracking, and flexible pricing, **[Helicone](https://www.helicone.ai/)** is the more versatile and accessible option. | ||
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| **For data scientists and ML engineers** working on complex LLM projects who require advanced evaluation capabilities and integration into existing ML workflows, **[Arize Phoenix](https://phoenix.arize.com/)** is preferable. |
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Same here with evals. we do that too!
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