Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
Integrations
Slack
APIFuzzer
CoLab
Codestral Mamba
Conda
Databricks
Declarative Webhooks
Haystack
JavaScript
JupyterLab
Integrations
Slack
APIFuzzer
CoLab
Codestral Mamba
Conda
Databricks
Declarative Webhooks
Haystack
JavaScript
JupyterLab
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