About Arize AI

Arize AI provides an AI observability and evaluation platform that enables developers to monitor, troubleshoot, and optimize large language models (LLMs) through performance tracing, data visualization, and automated evaluation workflows. The platform addresses issues of model performance degradation and data drift, ensuring that AI applications operate effectively and deliver reliable outcomes.

<problem> AI applications, particularly those powered by large language models (LLMs), often suffer from performance degradation, data drift, and unexpected behaviors in production. Identifying and resolving these issues requires extensive manual effort, hindering the ability to iterate and improve AI-powered products effectively. Current monitoring solutions lack the necessary tools for tracing, evaluating, and troubleshooting complex AI workflows. </problem> <solution> Arize AI offers an AI observability and evaluation platform designed to help developers monitor, troubleshoot, and optimize LLMs and other AI models. The platform provides end-to-end tracing, data visualization, and automated evaluation workflows to address model performance degradation and data drift. By leveraging these capabilities, AI engineers can quickly identify bottlenecks in LLM calls, understand agentic paths, and ensure AI behaves as expected. Arize AI enables proactive safeguards over AI inputs and outputs, surfacing insights and streamlining the process of identifying and correcting errors, ultimately improving the reliability and effectiveness of AI applications. </solution> <features> - End-to-end tracing to visualize and debug data flow in generative AI applications - Automated monitoring and dynamic dashboards to surface key metrics such as hallucination or PII leaks - AI-powered workflows to analyze and refine the performance of generative applications - Native support for experiment runs to accelerate iteration cycles for LLM projects - Prompt playground and management for testing changes to LLM prompts with real-time performance feedback - OpenTelemetry integration for robust, standardized instrumentation across the AI stack - Open-source LLM evaluations library and tracing code for seamless integration - AI-driven similarity search to find and analyze clusters of data points </features> <target_audience> Arize AI targets AI developers, data scientists, and machine learning engineers building and deploying AI-powered applications, including those using LLMs, who need to monitor, troubleshoot, and optimize model performance in production. </target_audience>

What does Arize AI do?

Where is Arize AI located?

Arize AI is based in Mill Valley, United States.

When was Arize AI founded?

Arize AI was founded in 2020.

How much funding has Arize AI raised?

Arize AI has raised 61020000.

Location

Mill Valley, United States

Founded

2020

Funding

61020000

Employees

102 employees

Major Investors

TCV

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Arize AI

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Executive Summary

arize.com 10K+

Crunchbase

Founded 2020 – Mill Valley, United States

Funding

Estimated Funding

$50M+

Major Investors

TCV

Team (100+)

No team information available.

Company Description

Problem

AI applications, particularly those powered by large language models (LLMs), often suffer from performance degradation, data drift, and unexpected behaviors in production. Identifying and resolving these issues requires extensive manual effort, hindering the ability to iterate and improve AI-powered products effectively. Current monitoring solutions lack the necessary tools for tracing, evaluating, and troubleshooting complex AI workflows.

Solution

Arize AI offers an AI observability and evaluation platform designed to help developers monitor, troubleshoot, and optimize LLMs and other AI models. The platform provides end-to-end tracing, data visualization, and automated evaluation workflows to address model performance degradation and data drift. By leveraging these capabilities, AI engineers can quickly identify bottlenecks in LLM calls, understand agentic paths, and ensure AI behaves as expected. Arize AI enables proactive safeguards over AI inputs and outputs, surfacing insights and streamlining the process of identifying and correcting errors, ultimately improving the reliability and effectiveness of AI applications.

Features

End-to-end tracing to visualize and debug data flow in generative AI applications

Automated monitoring and dynamic dashboards to surface key metrics such as hallucination or PII leaks

AI-powered workflows to analyze and refine the performance of generative applications

Native support for experiment runs to accelerate iteration cycles for LLM projects

Prompt playground and management for testing changes to LLM prompts with real-time performance feedback

OpenTelemetry integration for robust, standardized instrumentation across the AI stack

Open-source LLM evaluations library and tracing code for seamless integration

AI-driven similarity search to find and analyze clusters of data points

Target Audience

Arize AI targets AI developers, data scientists, and machine learning engineers building and deploying AI-powered applications, including those using LLMs, who need to monitor, troubleshoot, and optimize model performance in production.