Arize: LLM Observability and Evaluation Platform
Arize helps software companies and AI engineers manage the reliability of AI agents. It is designed for teams that need to identify hallucinations and monitor model drift in production.
At a glance
- Category
- Software Development
- Best for
- AI Engineers, Data Scientists, Software Companies, Enterprise AI Teams
- Pricing
- Pricing starts with free tiers (Phoenix OSS and AX Free), with a Pro tier available for $50 per month. Enterprise pricing requires a custom quote.
- Key use cases
- AI Agent Debugging, Prompt Iteration, Production Guardrails, Model Performance Analysis
- Integrations
- OpenTelemetry
- Official website
- arize.com/
Arize is an observability and evaluation platform for teams building and deploying AI agents and LLM-powered applications. It provides tools to trace data flow through a system and evaluate the quality of outputs to help bridge the gap between development and production.
The platform is designed for AI engineers and data scientists. It includes tools for identifying model failures, detecting drift, and optimizing prompts through a dedicated playground.
Buyers can use the platform for both generative AI and traditional machine learning and computer vision observability. It supports various workflows, from open-source tracing via Phoenix to enterprise monitoring and compliance.
Buyers should confirm their required data retention periods and span volumes, as these vary by pricing tier.
Key Features
Visualizes the flow of data through AI applications to identify bottlenecks and understand agent paths.
Supports online and offline assessments of task performance using LLM-as-a-Judge and custom templates.
Allows users to test prompt changes and view feedback against different datasets.
Monitors feature and embedding drift across training and production environments to identify performance shifts.
Provides workflows for identifying and correcting errors and managing labeling queues for dataset creation.
Uses dashboards and monitors to surface issues such as hallucinations or PII leaks.
Use Cases
Tracing multi-agent interactions to identify where a process failed or where a hallucination occurred.
Using the prompt playground to compare different prompt versions against a golden dataset.
Setting up monitors to detect PII leaks or performance regressions in a live AI application.
Using heatmaps and cluster search to identify underperforming data slices in ML models.
Best For
Integrations
Pricing
Pricing starts with free tiers (Phoenix OSS and AX Free), with a Pro tier available for $50 per month. Enterprise pricing requires a custom quote.
FAQ
Arize is used to monitor, debug, and evaluate AI agents and LLM applications. It helps teams trace data flows and detect performance issues like hallucinations or model drift.
Yes, Arize offers a free open-source version called Phoenix and a free SaaS tier (AX Free) for individuals and startups.
The platform is designed for AI engineers, data scientists, and software companies building production-ready AI agents.
Source category: Software Development
Source subcategory: Observability Platform
