International Space Station’s use of tabular AI and expanded partnerships demonstrate the art of the possible with SAP AI

BERLIN — SAP SE (NYSE: SAP) today announced a series of AI innovations at its annual SAP TechEd conference that expands its portfolio for developers.

The enhancements to the Joule Studio and Joule Work solutions and SAP Business AI Platform, including the latest tabular foundation model from SAP, offer new tools to build and extend AI agents, a richer data and business context for those agents to reason with, and strengthened governance controls to run them responsibly across the enterprise.

SAP Business AI Platform gives organizations one place to build, contextualize and govern AI across SAP and third-party environments. With Joule Studio, business users and developers can use no-code and pro-code tools to build and extend agents, choosing from more than 70 AI models. Customers in the Joule Studio early adopter program also can design and run n8n workflows in Joule Studio, with broader availability to follow. The SAP Business Data Cloud and SAP Knowledge Graph solutions ground those agents in trusted business data and context, helping organizations select the right model for each use case and better manage AI value and consumption. Importantly, SAP customers’ data remains their data. SAP does not share customer data with anyone to train or improve large language models.

“SAP TechEd has always been where builders shape what comes next,” said Philipp Herzig, CTO of SAP SE. “This year, we are showing how we are moving from AI learning your business to running it. Joule Work is where you put your intent and get work done, in one experience across the entire SAP landscape and beyond. That is the shift we are delivering at scale. Everything underneath runs on SAP Business AI Platform, delivering faster time to value through out-of-the-box business understanding, higher accuracy, enterprise-readiness that is secure, governed and compliant from the first deployment, and a unique context layer built on over 50 years of process and industry expertise, encoded into every agent action. This is AI built where real work happens.”

Joule Work and Joule Studio Make the Autonomous Enterprise Real

New capabilities for Joule Work will help make AI agents more effective at handling complex business processes via open protocols including Agent2Agent (A2A) and Model Context Protocol (MCP). These innovations advance Joule Work to better understand context, make decisions and execute multistep business workflows across enterprise systems and business domains:

• New agentic thinking capabilities that plan and orchestrate the steps assistants and agents need to reliably complete complex, multistep business workflows across SAP landscapes.
• New capabilities in SAP Knowledge Graph will incorporate data from additional SAP and non-SAP sources that are unique to each customer. Users can query and explore their customized data in natural language and get accurate answers grounded in their own information.
• Advancements in interoperability allow third-party agents to securely invoke Joule Agents through a governed agent gateway. This enforced access control enables agents from different providers to collaborate across business workflows without sacrificing governance or control.
• New SAP Enterprise AI Gateway solution will extend governance to AI interactions, offering a centralized way to manage AI traffic across the enterprise that will consolidate authentication, policy enforcement, routing, monitoring, usage tracking and auditing.
• New Joule Assistant and SAP AI Agent Hub expand governance capabilities, and a new AI Governance Assistant helps customers meet compliance requirements for the EU AI Act. These are designed to address critical barriers to scaling enterprise AI: keeping AI systems classified, compliant and operating within defined organizational guardrails and context.

SAP also announced that Joule Studio has new observability and administrative controls to give developers and administrators visibility into agent behavior, model usage and spend. Joule Studio is SAP’s AI-first development environment that is accessible through Joule Work for building and extending enterprise agents. Joule Studio will run a time-bound promotion for select customers, where deploying and running custom agents on the SAP-managed Joule Studio runtime will remain free through December 2026. The design-time tooling for building and testing agents and n8n workflows with AI-assisted development will remain free under fair-use limits.

SAP Business Data Cloud as the Grounding Engine of the Autonomous Enterprise

SAP Business Data Cloud Ontology Manager in SAP Business Data Cloud (SAP BDC) will provide an AI-native authoring experience for building ontologies across SAP and third-party data. By helping AI understand how data from different teams, systems and applications relate to one another, AI agents can more accurately reason and make decisions across the enterprise. The solutions complement SAP Knowledge Graph, which provides rich business context for SAP data.

Additionally, SAP is expanding its lakehouse capabilities with Dremio, adding native support for Apache Iceberg and Apache Polaris plus a high-performance, federated query engine that will enable unified data access without moving or copying the data. SAP expands its partnership with Databricks, bringing the full scope and latest innovations of data engineering and enterprise AI capabilities into SAP Business Data Cloud as SAP Databricks. Core innovations such as Lakeflow, Agent Bricks, Unity Gateway, and Lakebase will help customers to simplify data management and provide a strong data foundation for their AI journey. With a deeper integration to SAP Business Data Cloud, a new SAP Application Data Foundation, as well as an integration between Joule and Genie, SAP and Databricks are helping customers establish an enterprise-wide lakehouse as the foundation for the Autonomous Enterprise and Joule Work.

The SAP Reltio solution, recently announced at SAP Connect, will bring multidomain master data management to SAP BDC. It unifies and enriches customer, supplier and product records across SAP and non-SAP systems into trusted, reusable data products that can power applications and AI agents.

Tabular Foundation Model Trusted for Business, Validated in Space

SAP announced its latest tabular AI model, SAP-RPT-2.0, which will expand beyond classification and regression to support anomaly and outlier detection, and richer AI-powered analysis through embeddings. These native, multi-table capabilities will further reduce manual engineering while delivering faster, deeper insights from structured data. In addition, a new SAP-RPT-TS model will help customers predict values across time-indexed business metrics for key forecasting use cases using the SAP Integrated Business Planning solution without requiring custom machine learning.

In partnership with HPE, SAP also announced the deployment of SAP-RPT on the HPE Spaceborne Computer-2 aboard the International Space Station (ISS), one of the most significant edge-compute validations of any enterprise AI model to date. SAP-RPT is planned to run directly onboard the ISS to support anomaly triage, predict issues before failures escalate, reconstruct missing sensor values from historical data, and generate explainable mission-health reports for astronauts and ground teams — all without requiring data to be sent back to Earth for analysis.

“The same trusted SAP-RPT model that powers global supply chains also can work in space,” said Herzig. “SAP’s deep-rooted, proven expertise has led to the International Space Station’s use of our tabular foundation model to predict potential mission-critical failures in orbit. With SAP-RPT and TabPFN from Prior Labs, we bring the unique capabilities of tabular AI into the enterprise and across every frontier.”

Out-of-the-Box Assistants and Agents Define Our Advantage

For five decades, SAP has built the systems of record that run your business. We will deliver, out of the box, a suite of assistants and agents across five horizontal domains all running on SAP Business AI Platform — with industry specialization — that provides a baseline for systems of intelligence and systems of action.

Ecosystem Partners Help Expand Platform Capabilities

The global SAP partner ecosystem brings new capabilities to the ongoing operation and extension of solutions on SAP Business AI Platform, helping customers advance toward the Autonomous Enterprise. At SAP TechEd, the following partner announcements were highlighted:    

A collaboration with Intel closes the loop between enterprise workflows and autonomous robots, bridging informational technology and operational technology through physical AI.

In addition, new SAP solution extensions with Docusign, Parloa and Redwood extend autonomous capabilities for customers, helping them run their core processes end to end, without handoffs between systems.

Beyond technology, SAP is empowering its strong developer community with new enablement and engagement with tens of thousands joining for Devtoberfest leading up to SAP TechEd, new reference architectures, tutorials and hands-on opportunities attendees can try onsite at the event and at home.

To learn more about today’s announcements visit our SAP TechEd Innovation News Guide.

Visit the SAP News Center. Get SAP news via LinkedIn and Bluesky.

About SAP

As a global leader in enterprise applications and business AI, SAP (NYSE: SAP) stands at the nexus of business and technology. For over 50 years, organizations have trusted SAP to bring out their best by uniting business-critical operations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit www.sap.com.

Note to editors:
To preview and download broadcast-standard stock footage and press photos digitally, please visit www.sap.com/photos. On this platform, you can find high resolution material for your media channels.

For customers interested in learning more about SAP products:
Global Customer Center: +49 180 534-34-24
United States Only: 1 (800) 872-1SAP (1-800-872-1727)

For more information, press only:
SAP Press Room; press@sap.com

This press release was created with the assistance of artificial intelligence and has been reviewed by the editorial team.

This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of SAP’s 2024 Annual Report on Form 20-F.
© 2026 SAP SE. All rights reserved.
SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP SE in Germany and other countries. Please see https://www.sap.com/copyright for additional trademark information and notices.
Please consider our privacy policy. If you received this press release in your e-mail and you wish to unsubscribe to our mailing list please contact press@sap.com and write Unsubscribe in the subject line. 

Developers are being equipped to build, connect and govern enterprise AI, from intent to trusted execution.

Today, SAP announced the planned deployment of SAP-RPT, our tabular AI foundation model, on HPE Spaceborne Computer-2 aboard the International Space Station (ISS), one of the most significant edge-compute validations of an enterprise AI model to date. 

Space is unforgiving. Vacuum, radiation, orbital debris, and solar storms can produce mission-critical crises at any moment. Adding to the complexity, onboard sensors and mission system telemetry produce too much time-sensitive data to be routed back to Earth for analysis. Latency has to be reduced to ensure the safety of the spacecraft. 

Enter SAP’s tabular AI foundation model, SAP-RPT, which makes predictions directly from structured data—even with some data missing—and without requiring the usual model training or fine-tuning. Running directly onboard the ISS on HPE Spaceborne Computer-2, it supports anomaly triage in real-time telemetry data, predicts issues before failures escalate, reconstructs missing sensor values based on historical data, and generates explainable mission-health reports for astronauts and ground teams.

“This is proof that tabular AI on SAP works at the edge of possibility,” said Mayank Shrivastava, vice president of Generative AI and Foundation Models at SAP SE. “Space is the ultimate stress test for AI. If a foundation model can predict mission-critical failures in orbit, under radiation, energy, and connectivity constraints, imagine what it can do for a global enterprise. This is the same model that will predict supplier risk, cash flow anomalies, and equipment failures across your enterprise. What works in orbit works in your supply chain.” 

Imagine this: in orbit, data arrives in fragments, connectivity comes and goes, and you cannot send a technician when something starts to fail. You have to anticipate problems with a variety of signals. Enterprises face the same challenge on the ground: a supplier whose deliveries are quietly slipping, a payment pattern that’s drifting, a compressor that’s running hot. Predictive models that are able to spot early warning signs in a satellite are also built to find those same signals in your business data, so you can act before small problems become critical ones.

How SAP strengthens business functions with models for structured data 

SAP-RPT is part of SAP’s portfolio of tabular foundation models, or TFMs, that includes the TabPFN model by Prior Labs, and SAP AI Core, which orchestrates, manages, and governs TFMs, predictions, and workflows. Large language models (LLMs) excel at language and reasoning, but TFMs are built for the structured tabular data that underpin real-world operations, such as the sensor-driven data used in this project.  

SAP-RPT is about 50,000 times more energy-efficient than state-of-the-art LLMs. This is especially important in space, where every watt is constrained. SAP-RPT is also highly adaptable. It requires no pre-training as conditions evolve. 

Outcomes that will be delivered onboard include real-time predictions for computer and mission health status, an overall mission risk score, an assessment of whether manual intervention is needed, human-readable explanations of AI-driven findings, and ad hoc reports for crew and ground teams. 

“HPE Spaceborne Computer-2 continually demonstrates the advantages of having a high-performance compute solution aboard the ISS, supporting advanced technologies and on-going research in space” said Scott Wiest, Vice President and Global Sales Chief Technologist, HPE Fellow. “Deploying SAP’s tabular AI on HPE Spaceborne Computer-2 shows what’s possible with real-time detection and prediction using AI in the ultimate edge environment.” 

From orbit to enterprise 

The deployment of SAP-RPT on HPE’s Spaceborne Computer-2 on the ISS, by early 2027, will show how it strengthens business functions on earth. The constraints of space, including extreme energy limits, intermittent connectivity, radiation interference, and zero tolerance for failure are relevant to challenging use cases on earth. These include disaster relief operations, agriculture in remote areas, distributed manufacturing, and spread-out supply chains.  

Every insight aboard the ISS accelerates SAP’s road map for enterprise edge AI and key use cases that leverage structured data for the most important analytical and operational processes, even in the most challenging settings.  

Looking ahead, the mission lays the groundwork to support space-based data centers, deep space exploration, and other collaborations on space missions. Our long-term vision for space-based compute infrastructure is anchored in proven, efficient, and accurate AI. 

Explore how to deliver tabular AI on SAP, learn more about the specialized capabilities behind it, and try the SAP-RPT AI model with your own data on the Tabular AI area of sap.com. 

Brenda Bown is chief marketing officer for SAP Business AI Platform and Joule at SAP.

Most physical AI helps machines act. Physical AI by SAP helps businesses act. By linking robots and physical systems directly to the enterprise processes that run your organization, SAP turns physical execution into a governed, auditable extension of your business, extending the Autonomous Enterprise into the real world.

AI has gone from insight to action and now, with physical AI, it comes into the physical world.

Enterprises have made substantial investments in both AI and physical AI. AI helps business systems deliver remarkable insights and recommendations on financials, inventory, and supply chains. Physical AI creates value every day with physical systems—such as industrial robots, humanoids, sensors, or robot dogs—deployed across production lines, warehouses, field service teams, and logistics networks.

As automation, robotics, and sensing technologies have matured across industries, the volume and richness of the physical signals coming from physical execution has grown substantially; physical operations today generate continuous intelligence about factors such as asset health, task completion, quality, throughput, and exceptions.

Today, however, there is a gap between what the business knows and the intelligence generated by physical operations on the ground. This gap is one of the most common sources of operational friction across industries. It contributes to delayed responses, ill-informed decisions, and physical operations that never enter the business record. As a result, revenue and margins decrease while risk exposure increases.

From enterprise intelligence to physical action

This year at SAP TechEd, SAP revealed how our physical AI removes this operational friction: the system that runs your business is the same system that controls your physical operations.

The enterprise knowledge in your business system triggers the physical actions; physical signals arrive with the business context already attached; physical operations in the field flow back into SAP as structured data intelligence. Every physical action leaves a traceable, auditable record tied to the relevant business process.

The full context of your business is behind every physical action; verified outcomes are brought back into SAP in a secure and governed way for follow-up actions.

When the system that runs your business is also the system that governs how, when, and why physical tasks are executed, the result is a fundamentally different kind of operational capability. For enterprises already running SAP, this means physical execution inherits the intelligence, context, and governance already in place.

This is how physical AI by SAP transcends automation and extends the Autonomous Enterprise into the real world.

“Foxconn’s vision for intelligent manufacturing requires physical systems that understand business context, not just motion commands,” said Dr. Wang, head of Physical AI at Foxconn. “With physical AI by SAP, warehouse tasks from SAP Extended Warehouse Management directly orchestrate our humanoid robots and autonomous transport systems. Asset inspections triggered by maintenance plans flow to our robotic platforms and return verified outcomes back to SAP. This closed loop between enterprise systems and physical execution is what sets this collaboration apart: the robot knows why it acts, and the business system knows what happened.”

How physical AI by SAP capabilities are designed to transcend automation

1. Business-driven physical action

Physical AI is built to ground every physical execution in the business context: order priorities, safety rules, inventory status, and compliance constraints. Every action has a clear reason tied to business outcomes, and the business system remains in control of what gets executed, when, and why. The result is physical execution that is intelligent from the start, not just automated.

2. Physical evidence into digital workflows

Every physical task creates a complete audit trail and physical observations flow back into SAP automatically, transforming field outcomes into business insights rather than isolated records in a separate system. Physical world events become inputs to the decisions and processes that follow.

3. Enterprise-governed execution

Built on the SAP Business AI Platform, physical AI capabilities are designed to provide traceability, auditability, and human-in-the-loop control as first principles. Physical world data flows into SAP Business Data Cloud as new structured data products, enriching planning, predictions, and operational strategy over time.

4. Vendor and hardware agnostic

Working across device platforms, physical systems, and AI models of the customer’s choosing, customers retain freedom over their physical layer. SAP provides the business context, orchestration, and governance. Partners provide the physical execution.

Physical AI at work with customers and partners

Arçelik-LG: physical AI executes and records inbound storage tasks

Arçelik-LG is a joint venture between Turkish durable consumer, Arçelik and South Korea’s LG Electronics, manufacturing air conditioners. Physical AI by SAP enables a humanoid robot to execute and record inbound storage tasks. This has addressed the costly and persistent issue of incorrect storage placements in inbound logistics with potential savings of millions of euros.

• Associated SAP solutions: SAP Extended Warehouse Management
• Physical AI ecosystem partners: FairConsult 24|7
• Video: Arçelik-LG

Intel: physical AI in autonomous warehouse operations

Intel is one of the world’s largest semiconductor manufacturers, operating a vast global warehousing and logistics network and serves as both a  proof-of-concept environment and a technology collaborator. By integrating SAP’s enterprise workflows and warehouse processes with Intel-powered edge AI and robotics technologies, warehouse transport tasks generated in SAP are automatically translated into robot missions and executed autonomously in the warehouse.

SAP provides the business context, workflow governance, and process orchestration, ensuring that every physical action aligns enterprise priorities and operational goals. Intel provides the physical AI hardware and software foundation at the edge, delivering the compute AI and real-time robotics capabilities that enable autonomous systems to perceive, decide, and act in dynamic environments. The combined capabilities of SAP and Intel create a closed-loop system; business decisions become physical actions and operational outcomes are continuously fed back into business systems.

In a proof of concept demonstrated at Intel’s Chengdu site in China, material movement is automated end-to-end, reducing both transport distances and repetitive manual handling. Physical AI capabilities from SAP and Intel demonstrate how enterprise decisions can directly drive physical execution in logistics workflows.

• Associated SAP systems: SAP Extended Warehouse Management
• Physical AI ecosystem partners: Anu Intelligence

Holcim: industrial asset inspections

Holcim is a Swiss multinational building materials and sustainable construction company, operating in heavy industry. The company has significant infrastructure assets with inspection, maintenance, and safety use cases. Since attending the Embodied AI Jam held in August 2026, Holcim has implemented physical AI capabilities for asset inspections with industrial drones and quadruped dogs.

On-site quadruped dogs inspect conveyor belts in dark, dusty areas and the status of kilns in extreme temperatures. Drones inspect assets in heights difficult for humans to reach. And end-to-end automation starts and finishes in a SAP system. In SAP’s asset management solution, the maintenance plan triggers an action for the industrial drone/quadruped dog; once the action is executed, a maintenance notification is created back into SAP.

• Associated SAP systems: SAP Plant Maintenance
• Physical AI ecosystem partners: Cyberwave, Field AI, Hybird
• Video: Holcim

Start your physical AI journey today

From warehouse operations to asset maintenance, from safety inspections to keeping your operations compliant, physical AI capabilities from SAP have the potential to transform your business. It connects the intelligence of your enterprise with real-world execution; the SAP system that you trust to run your business is the same system that informs the actions of your physical systems, be it a robot, an industrial drone, or a robodog.

As a part of Industry AI, you can begin your physical AI journey today with warehouse operations and asset inspection use cases or a physical AI use case, tailor-made to your requirements. Contact SAP via email for more information.

Lukasz Ostrowski is global head of Physical AI and Robotics at SAP.