DataRobot and SAP Partner to Deliver Custom AI Solutions for the Enterprise

Today, SAP and DataRobot announced a joint partnership to enable customers connect core SAP software, containing mission-critical business data, with the advanced Machine Learning capabilities of DataRobot to make more intelligent business predictions with advanced analytics. Every modern enterprise has a unique set of business data collected as part of their sales, operations, and management processes. Leveraging DataRobot’s JDBC connectors, enterprise teams can work together to train ML models on their data residing in SAP HANA Cloud, as well as have an option to enrich it with data from external data sources. After a custom ML model is prepared, users can subsequently deploy these ML models to SAP AI core using automated model-deployment pipelines, and continue monitoring those models in production for accuracy and performance.

As a result, enterprises can now get powerful insights and predictive analytics from their business data by integrating DataRobot-trained machine learning models into their SAP-specific business processes and applications, while bringing data science and analytics teams and business users closer together for better outcomes.

More details about the joint capabilities were shared at the March 8^th SAP Data Unleashed virtual event and furthermore will be shared at From Vision to Value, Creating Impact with AI, the March 16^th DataRobot virtual event. Tune in to learn more. Registration is free for both events.

SAP AI Solutions: Making Business Applications More Intelligent

AI is at the heart of the SAP strategy to help customers become intelligent, sustainable enterprises. With SAP AI solutions such as SAP AI Core, AI Business Services and SAP HANA PAL, customers can bring predictive intelligence into their business processes through ready-to-use, pre-trained AI capabilities in SAP applications. 

Enterprises can extend AI capabilities to meet their specific needs, using SAP Business Technology Platform. They can also ensure trust and reliability by using AI capabilities that are built on a stringent ethics policy and data privacy standards that enable responsible use of AI with full transparency and compliance.

This partnership between the two brings together DataRobot’s multimodal machine learning capabilities with SAP’s extensive business data and processes to create business-centric ML solutions.

DataRobot AI: Complete AI Lifecycle Management

The DataRobot AI Platform is an open, complete AI lifecycle platform, leveraging machine learning that has broad interoperability, end-to-end capabilities for Experimentation and Production, and can be deployed on-premises or in any cloud infrastructure. 

DataRobot improves collaboration among AI teams so that they can discover and prove the value of models in business use cases through experimentation and then get models into production faster to improve how they run, grow, and optimize their business. Additionally, DataRobot data scientists and support teams have a proven record of success working with thousands of customers on tens of thousands of AI use cases across a wide range of industries.

DataRobot integration with SAP Datasphere enables customers to have quick access to their most updated, trusted, and governed data assets—with business context and logic intact.

Build Custom ML Models Combining Multimodal SAP and non-SAP Business Data

Every business has a unique data landscape and business processes that it wants to extract maximum value out of without causing too much disruption to its existing tech stack. So in order to get maximum value from AI, it needs to build machine learning models that are unique to each of its business usecase.

Here, it becomes crucial for the company to leverage an AI solution that can integrate with their existing workflows to ensure frictionless adoption by all stakeholders involved. 

With DataRobot’s built-in capability to connect to SAP HANA, users can quickly build custom AI models, using either the DataRobot user interface or DataRobot Notebooks for code-first data scientists. SAP customers can also ingest multimodal external data from other non-SAP sources, export DataRobot models into SAP AI Core through model-deployment pipelines, and use their predictions in SAP business applications, as well as continuously monitor and retrain models.

This joint solution thus helps enterprises get even more value out of their existing SAP and non-SAP business data by applying machine learning with broad interoperability across existing machine learning libraries and frameworks, and end-to-end capabilities for Experimentation and Production.

Enterprises can accelerate collaborative experimentation with the flexibility to customize models across open-source frameworks and production environments through a superior user experience, a decade of DataRobot’s data science expertise, and support for diverse organizational use cases. Using DataRobot, companies can monitor their models in production for accuracy and data drift, in addition to retraining them proactively. 

With DataRobot and SAP,  joint customers can:

leverage powerful machine learning on top of SAP Datasphere and bring it directly into their business data fabric – on whichever cloud platform it resides

facilitate collaborations between business teams and data science teams to create accurate and robust ML models and, more importantly, integrate predictions directly into SAP business applications through SAP AI Core

monitor model performance, regardless of where it is deployed, using DataRobot MLOps

detect and mitigate bias for more responsible use of ML models

SAP and DataRobot enable customers to connect core SAP software with DataRobot advanced machine learning capabilities. The result is more intelligent business predictions with advanced analytics.

Get Started with Business-Centric Machine Learning 

We are keen to collaborate with our customers and get feedback on our joint product roadmap as it evolves. 

You can learn more about today’s DataRobot and SAP announcements here:

• Visit datarobot.com/partners/technology-partners/sap

About the author

Ksenia Chumachenko

VP, Business Development & Alliances, DataRobot

Ksenia Chumachenko is a Vice President of Alliances and Business Development at DataRobot. She leads Cloud and Technology Alliances global team, helping clients get value from AI through a wider Cloud and Data ecosystem.

Ksenia has more than 20 years of experience delivering technological solutions and developing partner ecosystems across product startups, ISVs, and system integrators. She has passion for taking partnerships to the next level via collaboration, creativity, data-driven approach, and team nurturing with successful experience in establishing partner channel and building teams in pre- and post-IPO data startups.

Ksenia holds an MBA in Global Business and Entrepreneurship from NYU Stern School of Business, and B.S. in Computer Science and Mathematics from NYU Courant. In her free time she spends time in the San Francisco Bay Area with her family; they enjoy hiking, cooking and going to cultural events together.

Meet Ksenia Chumachenko

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Brian Bell Jr.

Senior Director of Product, AI Production, DataRobot

Brian Bell Jr. leads Product Management for AI Production at DataRobot. He has a background in Engineering, where he has led development of DataRobot Data Ingest and ML Engineering infrastructure. Previously he has had positions with the NASA Jet Propulsion Lab, as a researcher in Machine Learning with MIT’s Evolutionary Design and Optimization Group, and as a data analyst in fintech. He studied Computer Science and Artificial Intelligence at MIT.

Meet Brian Bell Jr.

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Anurag Sakhamuri

AI Success Manager, DataRobot

Anurag Sakhamuri is an AI Professional Services Manager. In his role, he helps his customers implement and integrate machine learning (ML) technologies to drive business value. He is an engineer and MBA by education and spent a good part of his career helping transform how enterprises operate using the latest technologies. He is passionate about helping customers (1) implement AI and ML technologies into their products and services, (2) automate and transform existing business processes and (3) apply data engineering advanced analytics to enable data-driven decision making. He has an undergraduate degree from Rutgers and an MBA from Kellogg – School of Management. Beyond his professional credentials, Anurag is an avid sports enthusiast and enjoys playing sports. He is also a traveler, having visited several countries across the world, and loves exploring new restaurants in New York City.

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