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Monday, March 4, 2024

DataRobot Joins the Amazon SageMaker Prepared Program


At DataRobot, we’re dedicated to serving to our clients maximize the worth they achieve from our AI Platform. At present, we’re excited to share that DataRobot has joined the Amazon SageMaker Prepared Program. This designation helps clients uncover companion software program options which are validated by Amazon Internet Providers (AWS) Associate Options Architects to combine with Amazon SageMaker. Our companion ecosystem is a key driver in guaranteeing buyer success, and partnering with AWS supplies clients with deep integrations that amplify the productiveness of information science groups. 

DataRobot and SageMaker create a strong 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 gather and monitor inference metrics. Monitoring jobs might be scheduled natively from DataRobot with out the trouble of guide pipelines, liberating up knowledge science assets whereas providing customers full observability throughout a lot of SageMaker fashions. Along with conventional MLOps actions, DataRobot AI Manufacturing provides 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 the environment and permits higher, sooner 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.

Bijan Beheshti

International Director, Analytics & Buying and selling, FactSet Analysis Methods

We’re thrilled to be a acknowledged Amazon SageMaker Prepared Associate, and stay up for serving to corporations obtain their expertise objectives 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 Associate Community (APN) member with a product that works with Amazon SageMaker and is usually out there for and absolutely helps AWS clients. The Amazon SageMaker Prepared program helps clients rapidly and simply discover AWS Software program Path companion merchandise to assist speed up their machine studying adoption by offering out-of-the-box abstractions for most typical challenges in machine studying (ML) that construct on prime of the foundational capabilities Amazon SageMaker supplies. 

Amazon SageMaker provides a sturdy set of capabilities and AWS Companions add worth to additional broaden the capabilities by integrating with their options. By offering clients a catalog of Software program Path companion options that elevate 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 clients Amazon SageMaker-supported merchandise that provide Amazon SageMaker each in Software program Path Associate options they already know, or provide merchandise that simplify every step of the ML mannequin constructing. These functions are validated by AWS Associate Options Architects to make sure clients have a constant expertise utilizing the software program.

To help the seamless integration and deployment of those options, AWS established the AWS Service Prepared Program to assist clients determine options that help AWS companies and spend much less time evaluating new instruments, and extra time scaling their use of options that work on AWS. Prospects can evaluation the Amazon SageMaker Prepared Associate product catalog to substantiate their most popular vendor options are already built-in with Amazon SageMaker. Prospects may also uncover, browse by class or ML mannequin deployment challenges, and choose companion software program options for his or her particular ML growth wants. 

White paper

Constructing a Scalable ML Mannequin Monitoring System with DataRobot and AWS


Obtain now

In regards to the creator

Ksenia Chumachenko
Ksenia Chumachenko

VP, Enterprise Improvement & Alliances, DataRobot

Ksenia Chumachenko is a Vice President of Alliances and Enterprise Improvement at DataRobot. She leads Cloud and Expertise Alliances world staff, 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 companion ecosystems throughout product startups, ISVs, and system integrators. She has ardour for taking partnerships to the following stage by way of collaboration, creativity, data-driven method, and staff nurturing with profitable expertise in establishing companion channel and constructing groups in pre- and post-IPO knowledge startups.

Ksenia holds an MBA in International Enterprise and Entrepreneurship from NYU Stern Faculty of Enterprise, and B.S. in Pc 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.


Meet Ksenia Chumachenko


Chen Wang
Chen Wang

Channel Information Scientist Director, DataRobot

Chen is Director of Associate Information Science at DataRobot, the place he drives product integration, demand era and buyer adoption via tech alliance and channel service companion ecosystem. He leads joint companion AI options to facilitate worth creation for patrons. Previous to DataRobot, Chen was at IBM main inside AI initiatives.


Meet Chen Wang

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