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NetApp Integration Solution

A Comprehensive MLOps, DevOps, and DataOps solution for data scientists and ML teams

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Increase productivity with an industry-first solution for ML dataset caching

With cnvrg.io and NetApp joint solution, datasets are ready to be used in seconds rather than hours. The solution improves sharing and collaboration for data science teams with cnvrg.io’s cached dataset capability that can be authorized and used by multiple teams in the same compute cluster connected to the NetApp cached data. Organizations using NetApp and cnvrg.io are able to reduce cost as machine learning models pull datasets from the cache, and not from remote storage, which may require payments per download. As a hybrid cloud solution dataset caching can present the on-premises mirror storage for the data lake residing in the cloud.

Accelerate ML workflows with automated MLOps, DevOps, and DataOps

Automate your machine learning Kubernetes infrastructure with a unique architecture that allows IT and engineers to attach different compute resources to one unified control plane, and manage ML jobs across all resources. Attach multiple on-premises Kubernetes clusters, VM servers, and cloud accounts and run ML workloads on all resources. 

Scale with hybrid machine learning
"Not only does cnvrg.io offer dynamic dataset caching at scale, but it also delivers a comprehensive AI OS for hybrid cloud data teams all the way from data to modeling to production. NetApp customers benefit from cnvrg.io's unique container-based architecture with integrated Kubernetes, and resource management systems enabling teams to utilize all their resources including NetApp's cloud connected high performance storage . We're excited to partner with cnvrg.io in providing a unified data fabric that increases productivity and reduces technical complexity and cost for enterprise data teams. Together with cnvrg.io we bring enterprise level AI through ONTAP AI and the rest of NetApp AI offerings from Edge to Core to Cloud”
Hoseb Dermanilian
Hoseb Dermanillian
Sr. Manager, WW AI Business Development, NetApp

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cnvrg- Data Science Platform
cnvrg.io - ML Platform

AI:OS for Machine Learning

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With cnvrg.io we were able to increase our model throughput by up to 50% and on average by 30% when comparing to RESTful APIs. cnvrg.io also allows us to monitor our models in production, set alerts and retrain with high-level automation ML pipelines
Avi Gabay
Avi GabayDirector of Architecture at Playtika
As with many data science professionals, our team is hard to please. They want the flexibility to use any language, and the ability to write their own custom packages to improve performance, set configurations, etc. With cnvrg.io, this is the first time I’ve heard our data scientists and analysts say ‘when can we have it’.
Alexander Ryabov
Alexander RyabovHead of Data Services & Business Intelligence at Wargaming.net
Working in a hybrid cloud environment has major advantages but can be increasingly complex to manage, especially for AI workloads. cnvrg.io has the potential to enable us to operate in a hybrid cloud environment seamlessly. The new ML infrastructure dashboard could fill a major need in connecting our infrastructure to ML projects. It provides visibility into our on-prem GPU clusters and cloud resources, paving the way for increasing the utilization and ROI of our GPUs.
Bruce King
Bruce KingData Science Technologist at Seagate Technology Advanced Analytics Group
Lightricks is a research-driven company, which is why we’ve built a team with some of the top computer vision researchers in the country. cnvrg.io ensures our highly qualified researchers are focused on building the industry-leading AI technology that we are now world renown for, instead of spending time on engineering, configuration and DevOps.
Ofir Bibi
Ofir BibiHead of Research at Lightricks
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