At DataRobot, we’re dedicated to serving to our prospects maximize the worth they achieve from our AI Platform. As we speak, we’re excited to share that DataRobot has joined the Amazon SageMaker Prepared Program. This designation helps prospects uncover associate software program options which are validated by Amazon Internet Providers (AWS) Companion Options Architects to combine with Amazon SageMaker. Our associate ecosystem is a key driver in guaranteeing buyer success, and partnering with AWS offers prospects with deep integrations that amplify the productiveness of information science groups.
DataRobot and SageMaker create a robust duo to speed up AI adoption
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 mechanically accumulate and monitor inference metrics. Monitoring jobs might be scheduled natively from DataRobot with out the trouble of guide pipelines, releasing up information science assets whereas providing customers full observability throughout a lot of SageMaker fashions. Along with conventional MLOps actions, DataRobot AI Manufacturing affords out-of-the-box governance finest practices corresponding to automated mannequin compliance documentation and mannequin versioning so all DataRobot and SageMaker fashions might be ruled centrally.
Collectively, DataRobot and AWS present a seamless integration that matches our surroundings and allows higher, sooner data-driven choices with confidence. As DataRobot and AWS now turn out to be 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 Companion, and look ahead to serving to corporations obtain their expertise targets by leveraging AWS. To be taught extra about DataRobot’s integration with Amazon SageMaker, obtain the whitepaper right here.
In regards to the SageMaker Prepared Program
Becoming a member of the Amazon SageMaker Prepared Program differentiates DatRobot as an AWS Companion Community (APN) member with a product that works with Amazon SageMaker and is usually out there for and totally helps AWS prospects. The Amazon SageMaker Prepared program helps prospects rapidly and simply discover AWS Software program Path associate 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 prime of the foundational capabilities Amazon SageMaker offers.
Amazon SageMaker affords a sturdy set of capabilities and AWS Companions add worth to additional increase the capabilities by integrating with their options. By offering prospects a catalog of Software program Path associate options that carry 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 provide Amazon SageMaker each in Software program Path Companion options they already know, or provide merchandise that simplify every step of the ML mannequin constructing. These purposes are validated by AWS Companion 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 companies and spend much less time evaluating new instruments, and extra time scaling their use of options that work on AWS. Clients can evaluate the Amazon SageMaker Prepared Companion product catalog to substantiate their most well-liked vendor options are already built-in with Amazon SageMaker. Clients may also uncover, browse by class or ML mannequin deployment challenges, and choose associate software program options for his or her particular ML growth wants.
In regards to the creator
Ksenia Chumachenko is a Vice President of Alliances and Enterprise Improvement at DataRobot. She leads Cloud and Expertise Alliances international group, serving to shoppers get worth from AI by a wider Cloud and Knowledge ecosystem.
Ksenia has greater than 20 years of expertise delivering technological options and creating associate ecosystems throughout product startups, ISVs, and system integrators. She has ardour for taking partnerships to the following degree through collaboration, creativity, data-driven strategy, and group nurturing with profitable expertise in establishing associate channel and constructing groups in pre- and post-IPO information startups.
Ksenia holds an MBA in International 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 together with her household; they take pleasure in mountaineering, cooking and going to cultural occasions collectively.
Chen is Director of Companion Knowledge Science at DataRobot, the place he drives product integration, demand technology and buyer adoption by tech alliance and channel service associate ecosystem. He leads joint associate AI options to facilitate worth creation for purchasers. Previous to DataRobot, Chen was at IBM main inner AI tasks.
