Enterprise software giant SAP SE is expanding its Business Data Cloud offering and doubling down on AI-ready data architectures, with product roll-outs and enhancements focused on bringing data and AI tools to developers and data engineers.

Today, during TechEd, the company’s annual event for developers and information technology professionals, SAP announced a slate of new data and AI capabilities. Announcements included new zero-copy integrations with Snowflake Inc., a visual Data Product Studio for enterprise data teams and a new tabular business data AI model.

In an interview with SiliconANGLE, Daniel Yu, chief marketing officer for SAP data and analytics, explained that a current roadblock for enterprise AI projects has become not just gathering up data but providing the proper context.

“With AI, you cannot really shy away from providing the right context of data. Now this has been very difficult and very costly,” said Yu. “Our goal is not to really move data into SAP or just provide data into a different platform, but bring the context and definition of data together.”

Modern-day businesses spend time sourcing data from disparate places, transforming it into usable formats, recreating schemas and applying context. But after that heavy lifting is done, business needs might have moved on or a trend changed. This means that when business users have new questions, additional context is needed to address them properly.

Databricks Inc. and Google Cloud with its BigQuery were the first partners to join SAP Business Data Cloud Connect, a service that eliminates the need for traditional extract, transform and load pipelines. ETL is a process used to combine data from different sources into a single, centralized data store, which enables business analysis and intelligence. It can also significantly slow access to fresh data. Connect allows the sharing of semantically rich data from SAP in real-time with customer platforms.

Today, SAP announced the addition of Snowflake, the cloud-based enterprise data warehouse platform, with access to the company’s Horizon catalog, combining it with data products within SAP. Through this partnership, customers will be able to preserve semantics, lineage and governance from SAP Business Data Cloud and receive detailed tracking of data usage, ownership and compliance support.

The addition of Snowflake is part of SAP’s strategy in bringing in major hyperscalers. Google LLC, Snowflake and Databricks today, but Yu said more will eventually come. This means that large-scale data sources such as Microsoft Corp.’s Azure and Amazon Web Services Inc. are on the horizon, but the company is not prepared to announce them.

Bringing data to businesses

SAP introduced the Data Product Studio, a new capability in its data cloud platform that will give developers and data teams a visual workspace to model, configure and manage custom data products.

It is a visual user interface for curating, versioning and combining enterprise data from various sources. Yu explained that most data engineers spend 80% of their time on data management and collection. With this solution, engineers will be able to visualize and control data sources from a catalog and, once they publish, view the entire lifecycle all the way to consumption.

“This will be a huge productivity gain for data engineering teams,” said Yu.

To better support business data, which is often delivered in tabular formats such as tables and information pulled from databases in rows and columns, SAP unveiled its first enterprise relational foundation AI model, SAP-RPT-1.

The new model, co-developed with Stanford University, was trained extensively on business relational and structured data. The model comes pretrained with the ability to assist customers, meaning that users will not need to prepare it to read and understand this sort of data. SAP said this makes it a ready-to-use endpoint for applications and business processes that require binary and multiclass classification as well as support numerical regression.

To give users a running start, SAP is also launching a web-based testing playground environment for the new model. It will be available at no cost, so customers can experience model performance and the model’s in-context learning capabilities, using their own data or SAP-provided example datasets.

SAP-RPT-1 will be generally available in the fourth quarter of 2025 via the company’s AI hub via SAP’s AI Foundation, with plans to roll out additional models in the family regularly.

“The end goal right now for most companies is to accelerate their AI journey,” Yu said. “I think that the flywheel effect between data, applications and AI means they all have to work together to make companies effective.”

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