During the annual IBM Think conference, IBM announced it is working with Amazon Web Services (AWS) to make the full portfolio of IBM offerings within the watsonx artificial intelligence (AI) and data platform available for use with AWS services. Today’s news will make it easier to scale AI in the enterprise using an open, hybrid approach supported by end-to-end governance.

The companies plan to integrate IBM watsonx.governance and Amazon SageMaker — a service to build, train, and deploy machine learning (ML) and generative AI models with fully managed infrastructure, tools, and workflows — to help Amazon SageMaker and watsonx customers manage model risk and support compliance obligations in connection with recent regulatory requirements such as the EU AI Act. This integration rounds out the availability of the watsonx platform in AWS Marketplace, which already includes IBM watsonx.ai and watsonx.data as customer managed offerings.

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“IBM’s open AI and hybrid cloud strategy is critical to helping businesses get value from AI, with their own trusted data, no matter what technology they use or where they’re using it,” said Ritika Gunnar, General Manager, Product Management, Data and AI, IBM. “Watsonx.governance enables them to manage and govern their AI solutions in an automated way, with the ability to customize solutions to their unique needs as they bring on more AI capability and respond to evolving AI regulations around the world. Our expanded relationship with AWS combines IBM’s leading AI governance with Amazon SageMaker, offering customers flexibility, scalability, and integration with other AWS services.”

Available in June, watsonx.governance and Amazon SageMaker will help clients streamline workflows, accelerate time to market for AI initiatives, and manage AI across complex IT environments and ecosystems. They will be able to configure and track fully customizable risk assessment and model approval workflows across multiple stakeholders, providing an audit trail in both watsonx and Amazon SageMaker.

“Balancing the rapid progression of generative AI with growing governance and regulatory concerns is a delicate challenge all organizations are concerned about,” said Chris Konow, CEO CleanSlate Technology Group, a cloud consulting company and AWS and IBM Business Partner. “The ability to seamlessly combine the power of AWS SageMaker with watsonx.governance will help address governance at the very foundation layer of AI projects.”

“IBM watsonx.governance on AWS provides fit-for-purpose AI governance capabilities that allow us to leverage the power of Amazon SageMaker,” said Adi Paz, CEO GigaSpaces Technologies, a provider of data platforms that enable natural language to query enterprise data. “Together these technologies create a highly trusted foundation for our Retrieval Augmented Generation Solution, GigaSpaces eRAG.”

Further supporting clients on their generative AI journey, watsonx.data is available on AWS to make it easier for customers to access, visualize and transform data for use in generative AI workloads. Through the watsonx.data open data lakehouse on AWS, customers can access data across hybrid environments including Db2 Warehouse, Netezza and Amazon Relational Database Service (Amazon RDS) for Db2, and AWS services such as Amazon Simple Storage Service (Amazon S3).

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In addition to the entire watsonx platform, IBM offers other software products and consulting offerings, including 44 listings, 29 SaaS offerings and 15 services, in AWS Marketplace across 92 countries. This includes the availability of a consumption-based license for Amazon RDS for Db2 to simplify workload management and enable faster cloud provisioning with on-demand licenses.

“Our collaboration with IBM will bring even more generative AI solutions to our mutual customers,” said Ankur Mehrotra, General Manager of Amazon SageMaker at AWS. “By combining the strengths of Amazon SageMaker and watsonx.governance, we are empowering businesses to leverage generative AI effectively and securely, drive workflow improvements, and ultimately deliver greater value. We look forward to continuing to innovate together on meaningful AI solutions for our customers.”

Amazon SageMaker HyperPod for Training IBM Models
Consistent with IBM’s hybrid cloud approach, IBM Research uses a combination of on-premises and cloud-hosted infrastructure to train the IBM Granite series of large language models. IBM utilizes its AI super computers to train its models and additionally has seen value in leveraging Amazon SageMaker HyperPod. Its seamless support for the open source tools and orchestrators enabled the IBM Research team to optimize and scale their training workload across the AWS environment.

IBM Consulting Brings Expertise to Create Responsible AI Frameworks
IBM Consulting is further expanding its generative AI expertise focused on AWS to help joint customers operationalize responsible AI. With the integration of watsonx.governance and Amazon SageMaker, IBM Consulting will be able to help joint clients establish a responsible AI framework to support their Amazon SageMaker initiatives across the enterprise – while managing model risk, demonstrating regulatory compliance and monitoring model performance.