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.
