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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

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

Sawmills stands out as the pioneering smart telemetry management platform that empowers businesses to manage their logs, metrics, and traces efficiently before incurring expenses from traditional observability tools. Its innovative use of AI for noise detection sets it apart from other solutions in the market, allowing Sawmills to effectively minimize waste, enhance data integrity, and enforce governance measures. Unlike conventional filtering methods and manually crafted rules, which often fall short in scalability, Sawmills leverages AI to analyze telemetry data in real-time, identifying noise patterns, duplicate events, low-value attributes, excessive cardinality, PII/policy breaches, and faulty schemas. For every issue detected, Sawmills suggests a corresponding action—options include filtering, redacting, aggregating, downsampling, normalizing, enriching, and it features the ability to auto-remediate with necessary approvals, service level agreements, and rollbacks. This proactive approach not only shifts oversight upstream but also significantly decreases waste, enhances the quality of the data being collected, and automates governance, ultimately leading to more efficient data management practices across enterprises.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Slack
APIFuzzer
CoLab
Codestral Mamba
Conda
Databricks
Declarative Webhooks
Haystack
JavaScript
JupyterLab
LlamaIndex
Mathstral
Ministral 8B
Mistral Large
Mistral NeMo
Mistral Small
Mixtral 8x22B
Mixtral 8x7B
Pixtral Large
Vercel

Integrations

Slack
APIFuzzer
CoLab
Codestral Mamba
Conda
Databricks
Declarative Webhooks
Haystack
JavaScript
JupyterLab
LlamaIndex
Mathstral
Ministral 8B
Mistral Large
Mistral NeMo
Mistral Small
Mixtral 8x22B
Mixtral 8x7B
Pixtral Large
Vercel

Pricing Details

Free
Free Trial
Free Version

Pricing Details

$0
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

Sawmills.ai

Founded

2024

Country

United States

Website

sawmills.ai

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