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February 5, 2019

ParallelM Provides Advanced Model Management and ML Health Monitoring for H2O Models

SUNNYVALE, Calif., Feb. 5, 2019 — ParallelM, a leader in MLOps, today announced integration with H2O open source to drive the adoption of AI across industries. The integrations will allow customers to quickly deploy and manage models in ParallelM MCenter and manage ongoing lifecycle needs like model health monitoring and model retraining for models running in production.

“As Gartner recently stated, H2O is effectively an industry standard in data science and machine learning. Part of our mission towards democratizing AI is to empower the ecosystem. As the H2O community continues to expand and grow, we are pleased that ParallelM is investing in H2O integration,” said Vinod Iyengar, Head of Data Science Transformation at “ParallelM provides advanced capabilities for model health monitoring and governance for all of the H2O community of customers.”

The initial integration, which is available now, makes it easy to import H2O models into MCenter in either the POJO or MOJO formats. Models can then be run in batch or real-time modes. Real-time models can take advantage of the new MCenter REST endpoint, a robust and scalable REST interface for production ML applications.

ParallelM also plans to integrate H2O models with instrumentation for the ParallelM MLOps API to generate model statistics without data scientists or even data analysts needing to touch the model code. This is particularly important for continuing democratization of AI as data analysts are creating more and more models using automatic machine learning systems like H2O Driverless AI.

ParallelM is also adding H2O as a natively supported engine for model retraining. With this integration, MCenter will be able to automatically trigger automated machine learning platforms like H2O AutoML and H2O DriverlessAI to retrain models. MCenter will then automatically import and deploy the new version without interrupting real-time serving or batch processing or requiring data scientists to be involved in the retraining process.

“ is a leader in the Data Science community and has changed the machine learning landscape with the introduction of H2O Driverless AI,” said Sivan Metzger, CEO, ParallelM. “We are excited to help customers bring more models into production with the introduction of a native MCenter integration for CI/CD, advanced ML health monitoring and Production Model Governance.”

About ParallelM

ParallelM is a company entirely focused on delivering machine learning operationalization (MLOps) at scale. ParallelM’s breakthrough MCenter solution is built specifically to power the deployment, optimization, and governance of machine learning pipelines in production so that companies can scale machine learning across their business applications. ParallelM’s approach is that of a single, unified MLOps solution that embeds best practice processes in technology, enabling all ML stakeholders to unlock the business value of AI. Please visit or email us at [email protected].

Source: ParallelM

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