Arize AI
MLOps platforms
- Features
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- Ease of management
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$50 per month
Free TrialFree version
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- Information technology and software
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What is Arize AI
Arize AI is an MLOps platform focused on model observability and evaluation for machine learning and generative AI systems in production. It helps ML engineers, data scientists, and platform teams monitor performance, detect data and concept drift, analyze errors, and investigate model behavior using telemetry and tracing. The product emphasizes production monitoring workflows (including LLM evaluation and prompt/response analysis) rather than end-to-end model development or data preparation. It is typically used alongside existing training pipelines and deployment infrastructure.
Strong model observability focus
Arize AI centers on monitoring and debugging models after deployment, including performance tracking, drift detection, and slice-based analysis. This focus fits teams that already have training and deployment tools but need production visibility. The platform supports workflows for investigating regressions and identifying segments where models underperform. It is positioned more as an observability layer than a full data science workbench.
LLM evaluation and tracing
Arize AI supports evaluation and monitoring patterns specific to LLM applications, such as prompt/response analysis and tracing of application interactions. This helps teams diagnose quality issues that are not captured by traditional classification/regression metrics. It aligns with production GenAI use cases where feedback signals are noisy and require structured evaluation. The tooling is oriented toward ongoing iteration rather than one-time benchmarking.
Integrates with existing stacks
Arize AI is commonly deployed as an add-on to existing data platforms, model training environments, and serving layers. This can reduce the need to replace established components used for feature engineering, training, or orchestration. Teams can instrument applications and models to send telemetry for monitoring and analysis. The approach suits organizations standardizing on separate best-of-breed components.
Not an end-to-end platform
Arize AI primarily addresses monitoring, evaluation, and debugging rather than the full lifecycle of data preparation, training, and deployment. Organizations seeking a single integrated environment for building and operationalizing models may need additional products for pipelines, notebooks, and governance. This can increase integration work across tools. Fit depends on whether the organization prefers a modular or consolidated stack.
Requires instrumentation and data quality
Effective use depends on instrumenting model services and applications to capture inputs, outputs, and relevant metadata. If teams cannot log features, predictions, ground truth, or user feedback reliably, monitoring and evaluation depth is limited. Implementation often requires coordination between ML, application, and platform engineering. Data privacy constraints can further restrict what can be logged and analyzed.
Cost and operational overhead
Production observability platforms can introduce additional operational overhead for data collection, storage, and retention of telemetry. Costs can grow with high-volume inference traffic and richer logging (for example, storing prompts and responses). Teams may need to tune sampling, retention, and metric definitions to manage spend. This trade-off is common when moving from basic dashboards to dedicated ML/LLM observability.
Plan & Pricing
| Plan | Price | Key features & notes |
|---|---|---|
| Phoenix (Self-hosted, open source) | Free (open source) | Self-hosted OSS option; Users: Unlimited; Trace spans, ingestion volume, projects, retention: user-managed; optional dedicated support add-on. |
| AX Free (SaaS) | Free | Single developer tier; 1 user; 25k spans/month; 1 GB ingestion/month; 7 days retention; includes online evaluations, product observability (monitors & custom metrics), community support. |
| AX Pro (SaaS) | $50 per month | Small teams/startups; Up to 3 users; 100k spans/month; 50 GB ingestion/month; Additional traces $10 per million; Additional ingestion $3 per GB; 15 days retention; includes Alyx Co-pilot, higher rate limits, email support; startup pricing available. |
| AX Enterprise (SaaS or Self-hosted) | Custom pricing | Enterprise-tier: Unlimited users; Billions+ trace spans; 5 TB+ ingestion (custom); configurable retention; dedicated support; uptime SLA; SOC2 & HIPAA compliance; training sessions; DataFabric/Data integrations; request trial/contact sales for pricing. |
Seller details
Arize AI, Inc.
Berkeley, CA, USA
2020
Private
https://arize.com/
https://x.com/arizeai
https://www.linkedin.com/company/arize-ai/
