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Hivecell, DataRobot partner to ease deployment, management of AI models

Hivecell, DataRobot partner to ease deployment, management of AI models

Edge-as-a-Service company Hivecell and DataRobot, an enterprise AI platform, have formed a partnership that is expected to enable enterprise organizations to solve bigger challenges at the edge by processing machine learning models on-site, outside of the data closet. By leveraging the two solutions, according to the announcement, organizations can more efficiently make relevant, data-driven decisions.

“We’re in the midst of an Intelligence Revolution and more and more organizations are looking to capitalize on the promise of AI and machine learning,” notes Jeffrey Ricker, co-founder and CEO at Hivecell. “DataRobot delivers AI at scale and by partnering with our team at Hivecell, we’re able to help ensure any AI models developed on their platform run as efficiently and effectively as possible. We’re excited by the partnership and even more eager to see the types of business outcomes that come from it.”

The DataRobot enterprise AI platform democratizes data science and drives automated decision intelligence, allowing organizations to deploy trusted and governed AI solutions to get from data to value faster and more accurately. Together, Hivecell and DataRobot empower organizations of any size, industry or resources to drive better business outcomes with AI by deploying onto Hivecell’s simple, scalable infrastructure. Organizations can deploy on premise compute power to hundreds or thousands of locations while managing them from one central location to provision, monitor and update complex frameworks remotely at half the cost of traditional cloud providers.

“We’re always looking to drive better business outcomes for our diverse customer base and we recognize the benefits, including reduced costs and improved bandwidth, edge computing brings to the AI lifecycle,” comments Dan Wright, CEO, DataRobot. “We’re pleased to team up with Hivecell to help organizations leverage machine learning models at the edge which will help them make faster, more accurate predictions that drive better business outcomes.”

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