Machine learning observability platform - AI tools

Censius is an AI observability platform that provides automated monitoring, proactive troubleshooting, and model explainability tools to help organizations build and maintain reliable machine learning models throughout their lifecycle.

• Free Trial

Superwise provides comprehensive ML observability to monitor, analyze, and maintain the health of machine learning models in production.

• Freemium

TruEra offers an AI observability and diagnostics platform to monitor and improve the quality of machine learning models. It aids in building trustworthy AI solutions across various industries.

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MLflow is an open-source, end-to-end MLOps platform for building better models and generative AI apps. It simplifies complex ML and generative AI projects, offering comprehensive management from development to production.

• Free

Openlayer provides a secure, SOC 2 Type 2 compliant platform for testing, evaluation, and observability of machine learning models. With its seamless, 60-second onboarding and commit-style versioning, it makes data-driven ML evaluation painless and effective.

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• API

Radicalbit is an MLOps and AI Observability platform that accelerates deployment, serving, observability, and explainability of AI models. It offers real-time data exploration, outlier and drift detection, and model monitoring.

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Evidently AI is a comprehensive AI observability platform that helps teams evaluate, test, and monitor LLM and ML models in production, offering data drift detection, quality assessment, and performance monitoring capabilities.

• Freemium
• From 50$

Laminar is an open-source platform that enables developers to trace, evaluate, label, and analyze Large Language Model (LLM) applications with minimal code integration.

• Freemium
• From 25$

Mona provides a Model Performance Insights Platform™ for proactive monitoring of AI, ML, and other data-driven systems in high-stakes environments.

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Valohai is an MLOps platform that streamlines complex machine learning workflows with CI/CD capabilities and pipeline automation, supporting on-premises and any-cloud environments.

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sizeless accelerates the development cycle of ML models, offering automated deployment, testing, and benchmarking. It's designed for ML engineers, researchers, and academics to streamline their workflow and improve model performance.

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Acceldata provides a unified data observability platform to ensure data quality, prevent failures, and control costs for hybrid and multi-cloud data stacks. It helps businesses build a strong AI foundation with high-quality, reliable data.

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