At DataRobot, we’re dedicated to serving to our prospects maximize the worth they acquire from our AI Platform. At the moment, we’re excited to share that DataRobot has joined the Amazon SageMaker Prepared Program. This designation helps prospects uncover accomplice software program options which might be validated by Amazon Net Companies (AWS) Accomplice Options Architects to combine with Amazon SageMaker. Our accomplice ecosystem is a key driver in making certain buyer success, and partnering with AWS supplies prospects with deep integrations that amplify the productiveness of information science groups.Â
DataRobot and SageMaker create a robust duo to speed up AI adoption Â
With DataRobot AI Manufacturing, customers can construct their very own SageMaker containers to coach AI fashions and host them as a SageMaker endpoint, leveraging DataRobot MLOps libraries to robotically gather and monitor inference metrics. Monitoring jobs may be scheduled natively from DataRobot with out the effort of handbook pipelines, liberating up information science assets whereas providing customers full observability throughout numerous SageMaker fashions. Along with conventional MLOps actions, DataRobot AI Manufacturing gives out-of-the-box governance finest practices akin to automated mannequin compliance documentation and mannequin versioning so all DataRobot and SageMaker fashions may be ruled centrally.Â
Collectively, DataRobot and AWS present a seamless integration that matches the environment and allows higher, quicker data-driven selections with confidence. As DataRobot and AWS now develop into much more aligned, the potential to additional leverage the strengths of each platforms with simplified workflows, enhanced scalability and accelerated time-to-market is tremendously thrilling.
We’re thrilled to be a acknowledged Amazon SageMaker Prepared Accomplice, and look ahead to serving to firms obtain their expertise objectives by leveraging AWS. To study extra about DataRobot’s integration with Amazon SageMaker, obtain the whitepaper right here.
Concerning the SageMaker Prepared Program
Becoming a member of the Amazon SageMaker Prepared Program differentiates DatRobot as an AWS Accomplice Community (APN) member with a product that works with Amazon SageMaker and is mostly accessible for and totally helps AWS prospects. The Amazon SageMaker Prepared program helps prospects rapidly and simply discover AWS Software program Path accomplice merchandise to assist speed up their machine studying adoption by offering out-of-the-box abstractions for commonest challenges in machine studying (ML) that construct on high of the foundational capabilities Amazon SageMaker supplies.Â
Amazon SageMaker gives a sturdy set of capabilities and AWS Companions add worth to additional develop the capabilities by integrating with their options. By offering prospects a catalog of Software program Path accomplice options that raise the complexities of machine studying, the Amazon SageMaker Prepared Program will broaden the person base and enhance buyer adoption. Amazon SageMaker Prepared Program members additionally provide AWS prospects Amazon SageMaker-supported merchandise that supply Amazon SageMaker each in Software program Path Accomplice options they already know, or provide merchandise that simplify every step of the ML mannequin constructing. These purposes are validated by AWS Accomplice Options Architects to make sure prospects have a constant expertise utilizing the software program.
To assist the seamless integration and deployment of those options, AWS established the AWS Service Prepared Program to assist prospects establish options that assist AWS providers and spend much less time evaluating new instruments, and extra time scaling their use of options that work on AWS. Prospects can assessment the Amazon SageMaker Prepared Accomplice product catalog to substantiate their most well-liked vendor options are already built-in with Amazon SageMaker. Prospects can even uncover, browse by class or ML mannequin deployment challenges, and choose accomplice software program options for his or her particular ML growth wants.Â
Concerning the writer
Ksenia Chumachenko is a Vice President of Alliances and Enterprise Growth at DataRobot. She leads Cloud and Know-how Alliances international crew, serving to shoppers get worth from AI via a wider Cloud and Information ecosystem.
Ksenia has greater than 20 years of expertise delivering technological options and creating accomplice ecosystems throughout product startups, ISVs, and system integrators. She has ardour for taking partnerships to the following stage through collaboration, creativity, data-driven strategy, and crew nurturing with profitable expertise in establishing accomplice channel and constructing groups in pre- and post-IPO information startups.
Ksenia holds an MBA in World Enterprise and Entrepreneurship from NYU Stern Faculty of Enterprise, and B.S. in Laptop Science and Arithmetic from NYU Courant. In her free time she spends time within the San Francisco Bay Space along with her household; they get pleasure from climbing, cooking and going to cultural occasions collectively.
Chen is Director of Accomplice Information Science at DataRobot, the place he drives product integration, demand technology and buyer adoption via tech alliance and channel service accomplice ecosystem. He leads joint accomplice AI options to facilitate worth creation for purchasers. Previous to DataRobot, Chen was at IBM main inside AI tasks.
