Arize Phoenix
An open-source LLM observability tool developed by Arize AI that supports tracing, evaluation, and experimentation for AI applications, with a focus on performance analysis of LLMs and agents.
Timeline (last 90 days)
The author used 24 Jev call samples to configure the prompt, evals, and dataset in Arize Phoenix.
The common industry standard for implementing traces is OpenTelemetry's GenAI semantic conventions, and platforms such as LangSmith, Langfuse, and Arize Phoenix are all compatible with this format.
Representative products in the LLM observability toolchain include LangSmith, Helicone, and Arize Phoenix.
Braintrust pricing starts free, with the Pro version at $249/month; Confident AI starts free, with the Starter version at $200/month; LangSmith starts free, with the Plus version at $39/seat/month; Langfuse is free, with paid versions starting at $29/month; Arize Phoenix is free, with the cloud version starting at $50/month; Galileo is free, with the Pro version starting at $100/month; LangWatch is free, with paid versions starting at €29/seat/month; Pydantic Logfire is free, with the Team version starting at $49/month; Latitude is free, with the Pro version at $99/month; Datadog LLM Observability is billed by usage; Fiddler is custom-quoted.
The article compared 12 AI agent observability and evaluation tools, including BotGauge, Braintrust, Confident AI, LangSmith, Langfuse, Arize Phoenix, Galileo, LangWatch, Pydantic Logfire, Latitude, Datadog LLM Observability, and Fiddler.
The industry has seen the emergence of observability platforms specifically for LLM applications, such as LangSmith, Langfuse, and Arize Phoenix, which can record the inputs and outputs, token consumption, and latency of each tool call.
Tools such as OpenTelemetry, LangSmith, and Arize Phoenix have begun standardizing the way Agent traces are collected.
Specialized tools such as LangSmith and Arize are filling the gaps in the LLM observability space
The industry has seen the emergence of observability platforms specifically designed for LLM applications, such as LangSmith, Langfuse, and Arize Phoenix.
The industry uses the OpenTelemetry standard or LLM observability platforms such as LangSmith, Langfuse, and Arize Phoenix to trace model inference inputs and outputs, token consumption, latency, and tool calls.
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All Facts (20)
The industry has seen the emergence of observability platforms specifically designed for LLM applications, such as LangSmith, Langfuse, and Arize Phoenix.
60%UnverifiedThe author used 24 Jev call samples to configure the prompt, evals, and dataset in Arize Phoenix.
50%UnverifiedThe common industry standard for implementing traces is OpenTelemetry's GenAI semantic conventions, and platforms such as LangSmith, Langfuse, and Arize Phoenix are all compatible with this format.
50%UnverifiedRepresentative products in the LLM observability toolchain include LangSmith, Helicone, and Arize Phoenix.
50%UnverifiedThe article compared 12 AI agent observability and evaluation tools, including BotGauge, Braintrust, Confident AI, LangSmith, Langfuse, Arize Phoenix, Galileo, LangWatch, Pydantic Logfire, Latitude, Datadog LLM Observability, and Fiddler.
50%UnverifiedBraintrust pricing starts free, with the Pro version at $249/month; Confident AI starts free, with the Starter version at $200/month; LangSmith starts free, with the Plus version at $39/seat/month; Langfuse is free, with paid versions starting at $29/month; Arize Phoenix is free, with the cloud version starting at $50/month; Galileo is free, with the Pro version starting at $100/month; LangWatch is free, with paid versions starting at €29/seat/month; Pydantic Logfire is free, with the Team version starting at $49/month; Latitude is free, with the Pro version at $99/month; Datadog LLM Observability is billed by usage; Fiddler is custom-quoted.
50%UnverifiedThe industry has seen the emergence of observability platforms specifically for LLM applications, such as LangSmith, Langfuse, and Arize Phoenix, which can record the inputs and outputs, token consumption, and latency of each tool call.
50%UnverifiedTools such as OpenTelemetry, LangSmith, and Arize Phoenix have begun standardizing the way Agent traces are collected.
50%UnverifiedSpecialized tools such as LangSmith and Arize are filling the gaps in the LLM observability space
50%UnverifiedThe industry uses the OpenTelemetry standard or LLM observability platforms such as LangSmith, Langfuse, and Arize Phoenix to trace model inference inputs and outputs, token consumption, latency, and tool calls.
50%UnverifiedMature AI observability tools such as LangSmith, Langfuse, and Arize Phoenix typically provide capabilities including tracing, cross-step input/output logging, token usage statistics, and anomaly replay.
50%UnverifiedPlatforms such as LangSmith, Langfuse, and Arize Phoenix have extended OpenTelemetry with LLM-specific enhancements, capable of recording token consumption, model versions, prompt content, and return results while providing trace replay.
50%UnverifiedLangfuse and Arize Phoenix are observability platforms that can be used to log Agent execution traces.
50%UnverifiedTools such as LangSmith, Langfuse, and Arize Phoenix have begun to offer tracing and evaluation capabilities, but structured measurement of task-level success remains a common industry shortcoming.
50%UnverifiedThe industry is converging on AI observability standards, such as OpenTelemetry's AI semantic conventions, as well as LLM-application-focused observability tools like LangSmith and Arize Phoenix.
50%UnverifiedTools such as LangSmith, Langfuse, and Arize Phoenix have specifically adapted the distributed tracing mechanism for LLM applications, supporting playback of an Agent's decision-making process by Trace.
50%UnverifiedEmerging Agent observability solutions such as LangSmith and Arize Phoenix have begun recording prompt/completion pairs from LLM calls and tool call inputs and outputs.
50%UnverifiedAgent observability tools include LangSmith, Arize Phoenix, and Weights & Biases Weave.
50%UnverifiedLangSmith, Langfuse, Arize Phoenix, Braintrust, and Helicone are observability and evaluation tools targeting LLM applications.
50%UnverifiedPlatforms such as LangSmith, Langfuse, Arize Phoenix, Braintrust, and Helicone help developers trace call chains, record token consumption, visualize prompt effects, and run offline evaluations.
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