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docs: update Arize agent evaluation resource URL #1164

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2 changes: 1 addition & 1 deletion aigw/integrations/tracing-providers/arize.mdx
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Expand Up @@ -13,7 +13,7 @@ Use Arize AX for production AI observability and evaluation. If you want an open

## Why the AI Gateway + Arize AX?

Thanks to OpenInference instrumentation, the AI Gateway can emit structured traces automatically. This gives you visibility into each LLM call routed through the gateway, making it easier to debug behaviour, inspect token usage, and evaluate production traffic in Arize AX. For production evaluation patterns, see Arize's [agent evaluation guide](https://arize.com/guides/ai-agent-handbook/agent-evaluation/) and [LLM evaluation guide](https://arize.com/resources/llm-evaluation/).
Thanks to OpenInference instrumentation, the AI Gateway can emit structured traces automatically. This gives you visibility into each LLM call routed through the gateway, making it easier to debug behaviour, inspect token usage, and evaluate production traffic in Arize AX. For production evaluation patterns, see Arize's [agent evaluation guide](https://arize.com/ai-agents/agent-evaluation/) and [LLM evaluation guide](https://arize.com/resources/llm-evaluation/).

<CardGroup cols={2}>
<Card title="AI Gateway Features" icon="shield">
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2 changes: 1 addition & 1 deletion aigw/integrations/tracing-providers/phoenix.mdx
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Expand Up @@ -5,7 +5,7 @@ description: "Open-source AI observability and evaluation with OpenInference ins

[Arize Phoenix](https://arize.com/phoenix/) is the open-source AI observability and evaluation platform from [Arize AI](https://arize.com/?utm_source=portkey-docs&utm_medium=partner&utm_campaign=partner-docs&utm_content=tracing-provider-phoenix). Use it for local development, OSS workflows, and self-hosted tracing with OpenInference instrumentation.

For the full-featured production platform built for AI-native teams and enterprises, use [Arize AX](https://arize.com/products/ax/) with the AI Gateway's [Arize AX integration](/aigw/integrations/tracing-providers/arize). AX is available as managed cloud or enterprise self-hosted deployment. Arize's [agent evaluation guide](https://arize.com/guides/ai-agent-handbook/agent-evaluation/) and [LLM evaluation guide](https://arize.com/resources/llm-evaluation/) show how traces support debugging, scoring, and continuous improvement workflows.
For the full-featured production platform built for AI-native teams and enterprises, use [Arize AX](https://arize.com/products/ax/) with the AI Gateway's [Arize AX integration](/aigw/integrations/tracing-providers/arize). AX is available as managed cloud or enterprise self-hosted deployment. Arize's [agent evaluation guide](https://arize.com/ai-agents/agent-evaluation/) and [LLM evaluation guide](https://arize.com/resources/llm-evaluation/) show how traces support debugging, scoring, and continuous improvement workflows.

<Info>
Phoenix's OpenInference instrumentation combined with the AI Gateway's intelligent gateway provides comprehensive debugging capabilities with automatic trace collection, while adding routing optimization and resilience features to your LLM calls.
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2 changes: 1 addition & 1 deletion integrations/tracing-providers/arize.mdx
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Expand Up @@ -13,7 +13,7 @@ Use Arize AX for production AI observability and evaluation. If you want an open

## Why Portkey + Arize AX?

Thanks to OpenInference instrumentation, Portkey can emit structured traces automatically. This gives you visibility into each LLM call routed through the gateway, making it easier to debug behavior, inspect token usage, and evaluate production traffic in Arize AX. For production evaluation patterns, see Arize's [agent evaluation guide](https://arize.com/guides/ai-agent-handbook/agent-evaluation/) and [LLM evaluation guide](https://arize.com/resources/llm-evaluation/).
Thanks to OpenInference instrumentation, Portkey can emit structured traces automatically. This gives you visibility into each LLM call routed through the gateway, making it easier to debug behavior, inspect token usage, and evaluate production traffic in Arize AX. For production evaluation patterns, see Arize's [agent evaluation guide](https://arize.com/ai-agents/agent-evaluation/) and [LLM evaluation guide](https://arize.com/resources/llm-evaluation/).

<CardGroup cols={2}>
<Card title="AI Gateway Features" icon="shield">
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2 changes: 1 addition & 1 deletion integrations/tracing-providers/phoenix.mdx
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Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,7 @@ description: "Open-source AI observability and evaluation with OpenInference ins

[Arize Phoenix](https://arize.com/phoenix/) is the open-source AI observability and evaluation platform from [Arize AI](https://arize.com/?utm_source=portkey-docs&utm_medium=partner&utm_campaign=partner-docs&utm_content=tracing-provider-phoenix). Use it for local development, OSS workflows, and self-hosted tracing with OpenInference instrumentation.

For the full-featured production platform built for AI-native teams and enterprises, use [Arize AX](https://arize.com/products/ax/) with Portkey's [Arize AX integration](/integrations/tracing-providers/arize). AX is available as managed cloud or enterprise self-hosted deployment. Arize's [agent evaluation guide](https://arize.com/guides/ai-agent-handbook/agent-evaluation/) and [LLM evaluation guide](https://arize.com/resources/llm-evaluation/) show how traces support debugging, scoring, and continuous improvement workflows.
For the full-featured production platform built for AI-native teams and enterprises, use [Arize AX](https://arize.com/products/ax/) with Portkey's [Arize AX integration](/integrations/tracing-providers/arize). AX is available as managed cloud or enterprise self-hosted deployment. Arize's [agent evaluation guide](https://arize.com/ai-agents/agent-evaluation/) and [LLM evaluation guide](https://arize.com/resources/llm-evaluation/) show how traces support debugging, scoring, and continuous improvement workflows.

<Info>
Phoenix's OpenInference instrumentation combined with Portkey's intelligent gateway provides comprehensive debugging capabilities with automatic trace collection, while adding routing optimization and resilience features to your LLM calls.
Expand Down
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