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Description
Phoenix serves as a comprehensive open-source observability toolkit tailored for experimentation, evaluation, and troubleshooting purposes. It empowers AI engineers and data scientists to swiftly visualize their datasets, assess performance metrics, identify problems, and export relevant data for enhancements. Developed by Arize AI, the creators of a leading AI observability platform, alongside a dedicated group of core contributors, Phoenix is compatible with OpenTelemetry and OpenInference instrumentation standards. The primary package is known as arize-phoenix, and several auxiliary packages cater to specialized applications. Furthermore, our semantic layer enhances LLM telemetry within OpenTelemetry, facilitating the automatic instrumentation of widely-used packages. This versatile library supports tracing for AI applications, allowing for both manual instrumentation and seamless integrations with tools like LlamaIndex, Langchain, and OpenAI. By employing LLM tracing, Phoenix meticulously logs the routes taken by requests as they navigate through various stages or components of an LLM application, thus providing a clearer understanding of system performance and potential bottlenecks. Ultimately, Phoenix aims to streamline the development process, enabling users to maximize the efficiency and reliability of their AI solutions.
Description
Netra serves as a robust platform designed for AI agents to monitor, assess, simulate, and enhance the decisions made by these agents, allowing for confident deployments and proactive identification of regressions prior to user exposure.
Key Features
1. Observability: Comprehensive tracing capabilities that capture every step of multi-agent, multi-step, and multi-tool processes, detailing inputs, outputs, timings, and costs for each reasoning step, LLM invocation, and tool use.
2. Evaluation: Automated quality assessment for each agent decision, utilizing integrated scoring rubrics, custom evaluations with LLMs and code reviewers, online assessments using live traffic, and continuous integration gates to prevent regressions.
3. Simulation: Evaluate agents under the stress of thousands of both real and synthetic scenarios before they go live. This includes using varied personas, conducting A/B tests against baseline performances, and quantifying confidence levels prior to any user interaction.
4. Prompt Management: Each prompt is versioned, compared, tracked for lineage, and safeguarded against rollbacks, ensuring that every production response can be traced back to its precise prompt version, thereby enhancing accountability and control.
In this way, Netra equips developers with the tools necessary to ensure the reliability and effectiveness of their AI systems.
API Access
Has API
API Access
Has API
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Integrations
Arize AI
CoLab
Codestral
CrewAI
Databricks
Gemini Enterprise Agent Platform
GitHub
Haystack
JavaScript
JupyterLab
Integrations
Arize AI
CoLab
Codestral
CrewAI
Databricks
Gemini Enterprise Agent Platform
GitHub
Haystack
JavaScript
JupyterLab
Pricing Details
Free
Free Trial
Free Version
Pricing Details
$39/month
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Arize AI
Country
United States
Website
docs.arize.com/phoenix
Vendor Details
Company Name
Netra
Founded
2025
Website
getnetra.ai/