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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
IBM Network Intelligence aims to enhance the transition towards an autonomous network lifecycle by providing instantaneous insights and operational automation across various vendors and domains. It employs network-native AI that is specifically trained on extensive telemetry data rather than generic datasets, merging analytical and reasoning functions to act as a cooperative partner rather than merely an observer. With its transparent and explainable AI decisions, it equips users with the assurance needed to understand the rationale behind each action taken. Built upon an open, interoperable framework, it seamlessly integrates with current tools and can function in on-premises, cloud, or hybrid settings without imposing vendor lock-in or necessitating complete system overhauls. From the outset, its pretrained models and swift ecosystem integration empower teams to reduce distractions by leveraging semantic understanding to highlight only actionable, high-confidence insights. This capability not only decreases the frequency of repeated incidents but also accelerates repair times and enhances overall mean time performance, ultimately streamlining network management. Thus, organizations can confidently adopt this cutting-edge technology to navigate the complexities of modern network environments more effectively.
API Access
Has API
API Access
Has API
Integrations
Amazon Bedrock
Codestral
Codestral Mamba
Conda
CrewAI
Databricks
JupyterLab
LangChain
LlamaIndex
Mathstral
Integrations
Amazon Bedrock
Codestral
Codestral Mamba
Conda
CrewAI
Databricks
JupyterLab
LangChain
LlamaIndex
Mathstral
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
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
IBM
Founded
1911
Country
United States
Website
www.ibm.com/products/network-intelligence