diff --git a/aigw/integrations/tracing-providers/arize.mdx b/aigw/integrations/tracing-providers/arize.mdx index 340c3ff5..570ede38 100644 --- a/aigw/integrations/tracing-providers/arize.mdx +++ b/aigw/integrations/tracing-providers/arize.mdx @@ -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/). diff --git a/aigw/integrations/tracing-providers/phoenix.mdx b/aigw/integrations/tracing-providers/phoenix.mdx index 4ed0e5c1..a315c85f 100644 --- a/aigw/integrations/tracing-providers/phoenix.mdx +++ b/aigw/integrations/tracing-providers/phoenix.mdx @@ -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. 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. diff --git a/integrations/tracing-providers/arize.mdx b/integrations/tracing-providers/arize.mdx index 5b75b79b..5c04c6f0 100644 --- a/integrations/tracing-providers/arize.mdx +++ b/integrations/tracing-providers/arize.mdx @@ -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/). diff --git a/integrations/tracing-providers/phoenix.mdx b/integrations/tracing-providers/phoenix.mdx index 28dc2179..0882b05f 100644 --- a/integrations/tracing-providers/phoenix.mdx +++ b/integrations/tracing-providers/phoenix.mdx @@ -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. 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.