Phoenix
Phoenix is an open-source AI development platform built on OpenTelemetry and OpenInference instrumentation, designed for AI engineers and Fortune 500 companies.
Publisher review
Phoenix is an open-source AI development platform built on OpenTelemetry and OpenInference instrumentation, designed for AI engineers and Fortune 500 companies. It provides comprehensive visibility into agentic applications, including LLM calls, tool executions, retrieval operations, and the complete agent reasoning loop. The platform is used by organizations such as Twilio, eBay, Microsoft, and Atlassian, and is available as a self-hosted open-source tool or a managed cloud service. It targets developers who need deep observability and evaluation capabilities, but is less suitable for non-tech-savvy users due to its technical complexity and self-hosting requirements.
Phoenix offers enterprise-grade features like statistical drift detection, distributed tracing, and a real-time hallucination firewall with sub-200ms blocking capability. Its Luna-2 SLMs achieve up to 97% cost reduction for evaluations. The platform includes built-in LLM evaluators, a prompt playground for experimenting with prompts, and the ability to create datasets and experiments from traces. It integrates with tools like Ragas, Deepeval, and Cleanlab, and supports human annotation for labeling traces directly in the UI. Cost tracking for token usage and costs is also built in, providing granular visibility into spending.
In the market, Phoenix competes with LangSmith, Langfuse, Braintrust, Helicone, and MLflow. It is recognized as a strong open-source alternative to proprietary platforms like LangSmith, particularly for teams that prioritize data autonomy and cost control. However, compared to Braintrust, Phoenix does not close the loop between production traces and evals; its cloud version still treats evals as disconnected from production data, forcing teams to build custom pipelines. Phoenix excels at showing what happened in production but lacks steps for automatic evaluation and improvement, a gap that competitors like Braintrust address.
The honest trade-offs: Phoenix offers 20% faster debugging and agent-native analytics, but self-hosting requires infrastructure overhead and technical expertise. The open-source version requires self-hosting, which can be a barrier for smaller teams. While the platform provides comprehensive evaluation frameworks, the cloud version still treats evals as disconnected from production data, limiting automated improvement. Additionally, Phoenix is less suitable for non-technical users, and its focus on observability over automated iteration means teams must invest in custom pipelines to fully leverage production insights.
How it works
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Distributed tracing
Provides visibility into every step of agentic applications, including LLM calls, tool executions, retrieval operations, and reasoning steps.
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Statistical drift detection
Enterprise-grade feature that monitors for statistical drift in model outputs, helping teams catch issues before they affect users.
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Built-in LLM evaluators
Includes pre-built evaluators to score outputs and catch issues, integrated with Ragas, Deepeval, and Cleanlab for extended evaluation.
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Prompt playground
Allows experimentation with prompts directly in the UI, enabling rapid iteration and testing before deployment.
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Datasets and experiments
Enables creation of datasets from traces and running experiments to test changes with evidence, supporting iterative improvement.
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Cost tracking
Tracks token usage and costs in real time, providing granular visibility into spending across LLM calls and tool executions.
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Human annotation
Supports labeling traces directly in the UI for human annotation, enabling manual quality assessment and feedback collection.
Strengths and trade-offs
Strengths
- Open-source platform with self-hosting option, giving teams full control over data and infrastructure.
- Real-time hallucination firewall with sub-200ms blocking capability, preventing issues before they reach users.
- Luna-2 SLMs achieve up to 97% cost reduction for evaluations, significantly lowering operational expenses.
- Agent-native analytics provide 20% faster debugging by showing every step an agent takes in the reasoning loop.
Trade-offs
- Self-hosting requires significant infrastructure overhead and technical expertise, making it less accessible for smaller teams.
- Cloud version still treats evals as disconnected from production data, forcing teams to build custom pipelines for automated improvement.
- Less suitable for non-tech-savvy users due to its technical complexity and reliance on OpenTelemetry instrumentation.
- Lacks built-in steps for automatic evaluation and improvement from production data, requiring manual intervention to close the loop.
Pricing context
Freemium: open-source version is free (self-hosted); cloud version has a free tier starting at $0/seat/month, with paid tiers for additional features and scale.
Getting started with Phoenix
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Sign up for Phoenix
Go to the Phoenix website and sign up for a free cloud account, or download the open-source version for self-hosting. Follow the registration prompts to create your account and verify your email.
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Connect your application
Install the OpenInference instrumentation library in your application. Configure it with your Phoenix endpoint and API key to start sending traces of LLM calls, tool executions, and agent steps.
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Configure drift detection
In the Phoenix UI, navigate to the monitoring settings and enable statistical drift detection. Set thresholds for model output changes to receive alerts when drift is detected.
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Run a trace evaluation
Select a trace from your production data in the UI. Use the built-in LLM evaluators to score the trace's outputs, or apply human annotation to label specific steps for quality assessment.
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Schedule cost tracking
Set up cost tracking by configuring token usage and cost parameters in the settings. Define a schedule for regular reports to monitor spending across all LLM calls and tool executions.
Frequently Asked Questions
What is Phoenix and what does it do?
Phoenix is an open-source AI development platform built on OpenTelemetry. It provides visibility into agentic applications, tracking LLM calls, tool executions, retrieval operations, and the complete agent reasoning loop for AI engineers and Fortune 500 companies.
How does Phoenix's hallucination firewall work?
Phoenix includes a real-time hallucination firewall that blocks problematic outputs in under 200 milliseconds. This enterprise-grade feature prevents issues before they reach users, catching hallucinations during inference to maintain output quality and safety in production environments.
Is Phoenix free to use?
Yes, Phoenix offers a freemium model. The open-source version is free and self-hosted, giving teams full data control. A managed cloud version also has a free tier starting at $0 per seat per month, with paid tiers for additional features and scale.
What are the main differences between Phoenix and LangSmith?
Phoenix is a strong open-source alternative to proprietary LangSmith, prioritizing data autonomy and cost control. However, Phoenix's cloud version treats evals as disconnected from production data, while LangSmith offers more integrated evaluation pipelines for automated improvement.
How does Phoenix track costs for LLM usage?
Phoenix includes built-in cost tracking that monitors token usage and costs in real time. It provides granular visibility into spending across LLM calls and tool executions, helping teams manage budgets and optimize resource allocation during development and production.
What are the weaknesses of using Phoenix?
Self-hosting Phoenix requires significant infrastructure overhead and technical expertise, making it less accessible for smaller teams. The cloud version also lacks automatic evaluation from production data, forcing teams to build custom pipelines for improvement. It is less suitable for non-technical users.
Alternatives
How Phoenix compares
Direct head-to-head against 3 competitors. Picked by 7wData.
Phoenix
- Pricing
- Freemium: open-source version is free (self-hosted); cloud version has a free tier starting at $0/seat/month, with paid tiers for additional features and scale.
- Target
- Phoenix is an open-source AI development platform built on OpenTelemetry and OpenInference instrumentation, designed for AI engineers and Fortune 500 companies.
- Strength
- Open-source platform with self-hosting option, giving teams full control over data and infrastructure.
- Watch for
- Self-hosting requires significant infrastructure overhead and technical expertise, making it less accessible for smaller teams.
Blueway
- Pricing
- Custom pricing, contact sales
- Target
- Business process management and automation
- Deployment
- Cloud, on-premises
- Strength
- Low-code BPM with strong governance features
- Watch for
- Limited third-party integrations reported
Airtable
- Pricing
- Free, Team $20/user/month, Business $45/user/month
- Target
- Workflow automation and database apps
- Deployment
- Cloud, mobile
- Strength
- Flexible spreadsheet-database hybrid interface
- Watch for
- Scaling beyond 50k records requires paid plans
Asana
- Pricing
- Free, Premium $10.99/user/month, Business $24.99/user/month
- Target
- Project and task management
- Deployment
- Cloud, mobile
- Strength
- Workflow automation with timeline views
- Watch for
- Limited BPM-specific process modeling
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Sources
Reporting on this tool draws on these publicly available sources.