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What is Stenograph Phoenix?

Phoenix serves as Stenograph's Automatic Speech Recognition (ASR) engine, designed specifically for the court reporting industry, and it leverages Stenograph's deep knowledge of legal vocabulary, formatting, and editing techniques. This powerful tool boosts reporters' efficiency and simplifies the transcript development process, resulting in increased productivity. When integrated with CATalyst Check It, Phoenix allows stenographers to swiftly identify inconsistencies between audio recordings and the written transcripts, which significantly minimizes the amount of typing required and makes text adjustments easier during editing, potentially saving around 45 minutes for each assignment. Furthermore, MAXScribe utilizes Phoenix's advanced speech technology and its specialized legal formatting capabilities, providing a thorough solution for recording, noting, translating in real-time, revising, and generating transcripts. With an impressive recognition accuracy of up to 94% for proper nouns, grammar, speaker identification, and understanding of questions and dialogue, Phoenix is an essential asset in the court reporting landscape. By delivering exceptional accuracy and operational efficiency, Phoenix not only assists court reporters in their tasks but also elevates the overall quality of legal documents, contributing to more reliable outcomes in legal proceedings. Its significance in the courtroom environment cannot be overstated, as it represents a blend of technological innovation and practical application in the pursuit of justice.

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.

Media

Media

Integrations Supported

MAXScribe

Integrations Supported

APIFuzzer
Amazon Bedrock
CoLab
Codestral Mamba
Conda
Gemini Enterprise Agent Platform
JupyterLab
LangChain
LlamaIndex
Mathstral
Ministral 8B
Mistral 7B
Mistral AI
Mistral Large
OpenAI
OpenTelemetry
Slack
Vercel

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Free
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

24 Hour Support
Web-Based Support

Training Options

Documentation Hub
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Stenograph

Date Founded

1938

Company Location

United States

Company Website

www.stenograph.com/phoenix

Company Facts

Organization Name

Arize AI

Company Location

United States

Company Website

docs.arize.com/phoenix

Categories and Features

Court Reporting

Not specified

Categories and Features

AI Observability

Not specified

LLM Evaluation

Not specified

Semantic Layer

Not specified

Telemetry

Not specified

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