Best-in-class Enterprise MLOps platform secures back-to-back recognition, paving the way for model-driven business around the world
SAN FRANCISCO, Feb. 15, 2023 /PRNewswire/ -- Domino Data Lab, provider of the leading Enterprise MLOps platform trusted by over 20% of the Fortune 100, today announced it was named to the Constellation ShortList™ for MLOps in Q1 2023. This marks the second year in a row that Domino has been recognized among leading MLOps solutions, demonstrating the company's dedication to helping its customers expedite data science innovation. The technology vendors and service providers included in this program deliver critical transformation initiative requirements for early adopters and fast-follower organizations.
As enterprises seek to implement artificial intelligence (AI) and machine learning (ML) models to scale their data science initiatives, the ability to efficiently develop, test, deploy and monitor those models in production is of the utmost importance. Today, Domino's enterprise MLOps platform is enabling the world's most sophisticated organizations to become model-driven; that is, to build and deploy more models in less time, demonstrating AI's value by improving products and processes, and positively impacting business results. This increases collaboration and governance to ease the IT department's burden of supporting AI at scale.
To enable greater participation and expand data science benefits, Domino is also now easing analyst and domain expert's transition to code. With the new Domino Code Assist, announced this week, companies can now expand their advanced analytics capability from within, empowering expert data scientists to lead and focus on the most complex challenges.
"The current trend of AI and ML breakthroughs is proof that playtime is over for data science," said Nick Elprin, co-founder and CEO of Domino Data Lab. "At Domino, we're proud to help our customers to scale and accelerate their data science journeys, and we're honored that Constellation Research has recognized the MLOps capabilities enabling them."
"Technology buyers making critical vendor selections look to Constellation's ShortLists to expedite the vendor selection process," said R "Ray" Wang, chairman and founder at Constellation Research. "Our analysts have done the hard work finding the best vendors in each category and validating with our buy-side clients. With each release, Constellation has saved organizations countless hours identifying the right solutions for their technology journey."
Constellation Research advises leaders on leveraging disruptive technologies to achieve business model transformation and streamline business processes. Products and services named to the Constellation ShortList meet the threshold criteria for this category as determined through client inquiries, partner conversations, customer references, vendor selection projects, market share, and internal research. The portfolio is updated at least once per year as the analyst team deems necessary based on market conditions.
For more information, visit https://www.constellationr.com/research/constellation-shortlist-mlops-0.
Additional Resources
- Visit the Domino Data Lab website to learn more about the Domino Enterprise MLOps Platform.
- Learn more about the Domino Enterprise MLOps Platform in the Domino Data Lab Blog.
- Follow Domino Data Lab on Twitter, LinkedIn and Facebook.
About Domino Data Lab
Domino Data Lab powers model-driven businesses with its leading Enterprise MLOps platform trusted by over 20% of the Fortune 100. Domino accelerates the development and deployment of data science work while increasing collaboration and governance. With Domino, enterprises worldwide can develop better medicines, grow more productive crops, build better cars, and much more. Founded in 2013, Domino is backed by Coatue Management, Great Hill Partners, Highland Capital, Sequoia Capital and other leading investors. For more information, visit www.dominodatalab.com
Disclaimer
Constellation Research does not endorse any solution or service named in its research.
SOURCE Domino Data Lab
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