SAP aims to displace more common language models with the release of its core “tabular” model, which the company claims will reduce training requirements for enterprises.
The model, called SAP RPT-1, is a pre-trained model with business and enterprise knowledge out of the box. SAP calls it a relational foundation model, meaning it can make predictions based on relational databases even with fine-tuning or additional training.
SAP’s global head of AI, Walter Sonn, told VentureBeat in an interview that the value of the new model lies in its ability to perform various enterprise tasks, such as predictive analytics, outside the box.
“Everybody knows about language models, and there are a bunch of good ones that already exist,” Sun said. “But we trained the model on data from business transactions, primarily Excel spreadsheets, and so we have a model that can do predictive analytics where the value is that it’s out of the box, meaning you don’t need any company details to work according to the language model.”
Right out of the gate, RPT-1 can essentially build a business model for enterprises based on data-driven knowledge from SAP’s decades of knowledge, Sun said. Organizations can plug the model directly into applications, even without additional fine-tuning.
RPT-1, SAP’s first major family of AI models, will be generally available in “Q4 of 2025” and will be deployed by SAP’s AI Foundation. While the RPT-1 is currently available, the company said additional models will be made available soon, including an open-source, state-of-the-art model.
SAP will also release a new code playground environment to experiment with the model.
Tabular model vs. LL.M
Tabular or relational AI models are learned from spreadsheets, unlike LLM, which is learned from text and code. RPT-1 not only understands the numbers and relationships between different cells, but is also able to provide more structured and precise responses.
When enterprises decide to use RPT-1, they can add more direction to the model with a little context engineering, because the model is implicitly aware and learns based on how it is being used.
SAP researchers first proposed the idea that tabular models can both exhibit semantic awareness and learn from content through paper. Published in June. It introduced context-aware presentation. It uses semantic cues such as table headers or column types to guide model training, enabling the model to build a relational structure with the data. It is this architecture that makes the model work best for tasks with precise answers, such as financial or enterprise use cases.
RPT’s models build on contextual work that allows it to learn structured business data, say from SAP’s knowledge graph, and then enable more context to be added through usage.
SAP researchers tested Context against the benchmark, saying it was “competitive” against similar models such as TabPFN and Tabfill.
The industry-specific model is increasing
Many enterprises have preferred to optimize general LLMs such as GPT5 or Cloud, to retrain models to answer questions primarily related to their business. However, to a shift Industry-specific models have begun to take root.
Sun said his experience at a previous company, building a very narrow, highly customizable AI model for sentiment analysis, inspired much of what makes RPT-1 different.
“It was a very customized model, a narrow model that took specific feedback for specific products but it wasn’t scalable,” Sun said. “When LLMS came out, it measured a model emotion. But there are use cases we can do that LLMS can’t.”
These use cases also include predictions, such as determining when a shopper will return to a grocery store, which can include an understanding of the shopper’s shopping habits as well as numerical analysis, he said. However, some LLMs have begun to integrate spreadsheets, and AI model providers encourage users to upload similar data to provide contextual learning. Microsoft Newly added COPILOT CAPABILITIESIncluding the ability to work in Excel. Anthropic Integrate his cloud Model with Excel, complementing it Claude for services to finance. Chinese startup familiar Also offers a Data visualization tool which understands spreadsheets, and ChatGPT can create charts from uploaded spreadsheets and other data sources.
However, SAP notes that it’s more than just reading a spreadsheet. RPT-1 should stand out among its competitors because it requires fewer additional pieces of information about a business to provide responses.