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What is Arize Phoenix?

Phoenix is an open-source library designed to improve observability for experimentation, evaluation, and troubleshooting. It enables AI engineers and data scientists to quickly visualize information, evaluate performance, pinpoint problems, and export data for further development. Created by Arize AI, the team behind a prominent AI observability platform, along with a committed group of core contributors, Phoenix integrates effortlessly with OpenTelemetry and OpenInference instrumentation. The main package for Phoenix is called arize-phoenix, which includes a variety of helper packages customized for different requirements. Our semantic layer is crafted to incorporate LLM telemetry within OpenTelemetry, enabling the automatic instrumentation of commonly used packages. This versatile library facilitates tracing for AI applications, providing options for both manual instrumentation and seamless integration with platforms like LlamaIndex, Langchain, and OpenAI. LLM tracing offers a detailed overview of the pathways traversed by requests as they move through the various stages or components of an LLM application, ensuring thorough observability. This functionality is vital for refining AI workflows, boosting efficiency, and ultimately elevating overall system performance while empowering teams to make data-driven decisions.

What is Apache Ossie?

Apache Ossie functions as an open specification and conversion toolkit that facilitates the effortless sharing of semantic metadata among analytics, business intelligence, and AI systems. By employing a YAML-based format, it defines semantic models, datasets, fields, metrics, dimensions, relationships, and SQL expressions in a format that is straightforward to transfer. This capability allows data and analytics engineers to formulate, convert, and adapt these definitions across interconnected platforms, thereby promoting a cohesive business context for both reporting and AI-driven analysis. Operating as a collaborative project under the Apache License 2.0, the availability of various conversions relies on the specific implementations by individual platforms. Furthermore, this initiative nurtures collaboration and innovation within the open-source community, motivating contributions that can further enhance the functionality and effectiveness of the toolkit. Overall, Apache Ossie stands as a pivotal resource for organizations aiming to streamline semantic metadata management across diverse systems.

Media

Media

No images available

Integrations Supported

Databricks
Amazon Bedrock
Codestral Mamba
Gemini Enterprise Agent Platform
Guardrails AI
Haystack
LlamaIndex
Mathstral
Ministral 3B
Ministral 8B
Mistral 7B
Mistral AI
OpenAI
Python

Integrations Supported

Databricks
Cube
Holistics
Omni
Sigma
WisdomAI
dbt

API Availability

Has API

API Availability

Pricing Information

Free
Free Version

Pricing Information

Pricing not provided
Free Version

Supported Platforms

SaaS

Supported Platforms

Not specified

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Arize AI

Company Location

United States

Company Website

docs.arize.com/phoenix

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

ossie.apache.org

Categories and Features

AI Observability

Not specified

LLM Evaluation

Not specified

Semantic Layer

Not specified

Telemetry

Not specified

Categories and Features

Semantic Layer

Not specified

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