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Aporia Partners with Databricks to Empower Organizations to Monitor ML Models in Real Time

Aporia, the leading ML Observability platform, announced a partnership with Databricks, the data and AI company allowing organizations to unify their data, analytics, and AI. The strategic partnership will provide seamless ML Observability to customers using Databricks’ Lakehouse Platform, AI capabilities, and MLflow offerings.

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With Aporia, Databricks customers can now monitor their ML models in production without duplicating any data from their Lakehouse or any other data source. Aporia’s quick deployment on Databricks enables monitoring billions of predictions without data sampling, production code changes, or hidden storage costs.

To monitor large amounts of data, organizations often need to duplicate data from their data lake to their monitoring platform. However, this often leads to highly inaccurate results with issues going unnoticed, drift and false positive alerts, and difficulties in properly monitoring for bias and fairness. Aporia’s integration with Databricks allows organizations to monitor all of their machine learning models on Databricks in just a few minutes, leveraging their existing database investment — even for use cases that require processing large volumes of predictions, such as recommendation systems, search ranking models, fraud detection models, and demand forecasting models.

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“As the AI market rapidly expands, there’s a growing demand for effective tools to monitor and maintain machine learning models in production,” said Liran Hason, CEO of Aporia. “Aporia’s integration with Databricks expedites the adoption of Observability as a critical component for organizations investing in AI and Machine Learning. Our partnership allows us to provide a solution that is both centralized and cost-effective, addressing a critical need for our clients and empowering them to make data-driven decisions.

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