麻豆原创 has announced a series of AI innovations at its annual 麻豆原创 TechEd conference, expanding its portfolio for developers. The enhancements to Joule Studio and Joule Work, as well as the 麻豆原创 Business AI Platform 鈥� including 麻豆原创’s latest tabular foundation model 鈥� offer new tools to build and extend AI agents.

麻豆原创 said its strategy is to advance the development and adoption of agentic AI by providing richer business and data context for agents, and governance controls to manage their use across organisations.

Philipp Herzig, CTO of 麻豆原创 SE, said the 麻豆原创 Business AI Platform, along with 麻豆原创 Knowledge Graph, 麻豆原创 Business Data Cloud, Joule Studio, Joule Work and agentic orchestration and integration capabilities, is now generally available.

鈥淭his entire platform is now generally available with all its capabilities, starting at the top with Joule Work, available on every device, every computer, in every browser. Joule Work is where you put your intent and get work done, in one experience across the entire 麻豆原创 landscape and beyond. That is the shift we are delivering at scale. Everything underneath runs on 麻豆原创 Business AI Platform.鈥�

Asked how 麻豆原创 connects with external AI agents entering the market and supports customers already using agents from other vendors, Herzig said the company follows an open strategy.

鈥淐ustomers say that if 麻豆原创 provides an agent in the core domains where they have 麻豆原创, there鈥檚 no need to build and own one. There are tons of agents out there, and we have made sure, via our agent gateway, that there is full interoperability. Our AI agent hub allows you to discover the agents, 麻豆原创 agents and non-麻豆原创 agents, and you can document them and make them compliant.鈥�

Herzig also addressed vendor lock-in and the challenges organisations face when using AI models from different vendors, discussing 麻豆原创鈥檚 approach to letting customers select models for specific use cases.

He said that tailoring a use case for optimisation inevitably brings some lock-in, but that model switchability remains viable for organisations keeping their AI use cases fairly generic.

AI to serve autonomous enterprise operations

Florian Kunzke, global director of AI strategy at 麻豆原创, echoed Herzig鈥檚 view that the company is moving from AI that learns how a business operates to AI that runs it, with the objective of mobilising AI to serve autonomous enterprise operations.

He said 麻豆原创鈥檚 AI strategy continues to evolve, particularly from a user interface and user experience point of view, with agents embedded in its technology suite.

Kunzke said Joule Work and Joule Studio, alongside 麻豆原创 Knowledge Graph 鈥� which provides a structured semantic foundation for Joule 鈥� are central to 麻豆原创鈥檚 AI strategy. The company aims to help organisations become autonomous enterprises while addressing challenges such as the impact of geopolitical tensions on supply chains, the need to improve productivity through AI investment, and the requirement to generate ROI.

He cited , released in August 2026. According to the research, 80% of respondents said AI had improved individual productivity, while 50% said it helped them make better decisions.

However, he stressed the need for perspective on how AI is being adopted and used across organisations. 鈥淚t is important to distinguish between what happens at organisational level and what happens at individual level. There is a gap, and that is what 麻豆原创 is looking to address,鈥� said Kunzke.

He also acknowledged that shadow AI, rogue AI, cyber security threats and the maturity of digital infrastructure continue to affect AI adoption. However, he added that 麻豆原创 is confident its technology empowers customers to select the right AI for a job, as well as the necessary level of control.

鈥淵ou can improve what you are able to observe and measure. With agentic solutions and processes, and the adoption of these processes, the question is what to aim for in terms of governance, what tools will the organisation need. It makes sense to have tools be as close as possible to the applications being used.鈥�

Independent AI expert Johan Steyn, founder of , said the shift to agentic AI marks an inflexion point. “AI strategy stops being about which tools you buy and becomes about how you orchestrate and govern agents,” he said. “Capability is becoming abundant; governance is the scarce advantage.”

Latest tabular AI model

麻豆原创 announced its latest tabular AI model, 麻豆原创-RPT-2.0, which will expand beyond classification and regression to support anomaly and outlier detection, and richer AI-powered analysis through embeddings.

According to 麻豆原创, these native, multi-table capabilities will further reduce manual engineering while delivering faster, deeper insights from structured data.

In partnership with HPE, 麻豆原创 also announced plans to deploy 麻豆原创-RPT-2.0 on the HPE Spaceborne Computer-2 aboard the International Space Station (ISS) in 2027.

The model is scheduled to run directly on the ISS to support anomaly triage, predict potential problems before failures escalate, reconstruct missing sensor values using historical data, and generate mission-health reports for astronauts and ground teams.

Herzig added: 鈥淭he same trusted 麻豆原创-RPT model that powers global supply chains can also work in space. 麻豆原创鈥檚 deep-rooted, proven expertise has led to the International Space Station鈥檚 use of our tabular foundation model to predict potential mission-critical failures in orbit. With 麻豆原创-RPT and TabPFN from Prior Labs, we bring the unique capabilities of tabular AI into the enterprise and across every frontier.鈥�

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麻豆原创 Business AI Platform gives organizations one place to build, contextualize and govern AI across 麻豆原创 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 麻豆原创 Business Data Cloud and 麻豆原创 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, 麻豆原创 customers鈥� data remains their data. 麻豆原创 does not share customer data with anyone to train or improve large language models.

鈥溌槎乖� TechEd has always been where builders shape what comes next,鈥� said Philipp Herzig, CTO of 麻豆原创 SE. 鈥淭his 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 麻豆原创 landscape and beyond. That is the shift we are delivering at scale. Everything underneath runs on 麻豆原创 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.鈥�

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 麻豆原创 landscapes.
• New capabilities in 麻豆原创 Knowledge Graph will incorporate data from additional 麻豆原创 and non-麻豆原创 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 麻豆原创 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 麻豆原创 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.

麻豆原创 Business Data Cloud as the Grounding Engine of the Autonomous Enterprise

麻豆原创 Business Data Cloud Ontology Manager in 麻豆原创 Business Data Cloud (麻豆原创 BDC) will provide an AI-native authoring experience for building ontologies across 麻豆原创 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 麻豆原创 Knowledge Graph, which provides rich business context for 麻豆原创 data.

Additionally, 麻豆原创 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. 麻豆原创 expands its partnership with Databricks, bringing the full scope and latest innovations of data engineering and enterprise AI capabilities into 麻豆原创 Business Data Cloud as 麻豆原创 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 麻豆原创 Business Data Cloud, a new 麻豆原创 Application Data Foundation, as well as an integration between Joule and Genie, 麻豆原创 and Databricks are helping customers establish an enterprise-wide lakehouse as the foundation for the Autonomous Enterprise and Joule Work.

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

Tabular Foundation Model Trusted for Business, Validated in Space

麻豆原创 announced its latest tabular AI model, 麻豆原创-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 麻豆原创-RPT-TS model will help customers predict values across time-indexed business metrics for key forecasting use cases using the 麻豆原创 Integrated Business Planning solution without requiring custom machine learning.

In partnership with HPE, 麻豆原创 also announced the deployment of 麻豆原创-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. 麻豆原创-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 鈥� all without requiring data to be sent back to Earth for analysis.

鈥淭he same trusted 麻豆原创-RPT model that powers global supply chains also can work in space,鈥� said Herzig. 鈥溌槎乖粹�檚 deep-rooted, proven expertise has led to the International Space Station鈥檚 use of our tabular foundation model to predict potential mission-critical failures in orbit. With 麻豆原创-RPT and TabPFN from Prior Labs, we bring the unique capabilities of tabular AI into the enterprise and across every frontier.鈥�

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

For five decades, 麻豆原创 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 麻豆原创 Business AI Platform 鈥� with industry specialization 鈥� that provides a baseline for systems of intelligence and systems of action.

Ecosystem Partners Help Expand Platform Capabilities

The global 麻豆原创 partner ecosystem brings new capabilities to the ongoing operation and extension of solutions on 麻豆原创 Business AI Platform, helping customers advance toward the Autonomous Enterprise. At 麻豆原创 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 麻豆原创 solution extensions with , and extend autonomous capabilities for customers, helping them run their core processes end to end, without handoffs between systems.

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

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Held virtually on 3 September 2026, the session, 麻豆原创鈥檚 鈧�100M AI Opportunity: How to Secure Funding for Your Next AI Project, brought together 麻豆原创 experts , , , and to unpack the opportunity, eligibility requirements and practical process for accessing the incentive.

The discussion came at an important time for organisations exploring artificial intelligence. While investment and interest in AI continue to accelerate, many organisations are still struggling to translate experimentation into sustainable business value. The presentation highlighted that data access and quality remain significant barriers, while many organisations remain caught in pilot mode without a clear path to scale.

From AI experimentation to business value

A key message from the session was the need to move beyond isolated AI use cases towards AI that is embedded into business processes, supported by appropriate governance and connected across the organisation.

麻豆原创 described the evolution towards an autonomous enterprise where agents can support routine transactions and coordinate actions across business processes, while people remain focused on higher-value decisions. Importantly, governance, auditability and traceability need to be built into AI-enabled processes from the outset.

The webcast also reinforced the importance of keeping people at the centre of AI adoption, with human-triggered and monitored agent actions forming part of understanding the 鈧�100 million opportunity

At the heart of the webcast was 麻豆原创鈥檚 鈧�100 million Business AI Partner-led Adoption Incentive, a pilot programme aimed at helping customers realise greater value from their 麻豆原创 Business AI investments by encouraging adoption and consumption through the 麻豆原创 partner ecosystem.

Approved partners can deliver projects across 麻豆原创 Business AI, including 麻豆原创 Build and Joule Studio, creating agents, applications and workflows around customer use cases. The programme is running through the end of 2026.

The programme includes different levels of support depending on the scope of the implementation, ranging from 鈧�15,000 for 麻豆原创 Agent Adoption, through 鈧�25,000 and 鈧�50,000 packages, to an 鈧�100,000 Enterprise Package supporting three or more custom Joule Studio or 麻豆原创 Build agents together with workflow or pro-code application development.

Who can participate?

The session also provided clarity on customer eligibility. The programme is aimed at qualifying existing 麻豆原创 Business AI Platform customers with active subscriptions as well as certain new customers entering eligible 麻豆原创 Business AI Cloud Services agreements during the programme period. Specific commercial and subscription criteria apply, while public-sector and government entities are excluded from the current programme.

Customers do not apply independently. Eligible customers are nominated through an 麻豆原创 representative, after which 麻豆原创 validates programme eligibility. Once approved, customer consent is obtained before enrolment.

Importantly, the final choice of implementation partner remains with the customer. Customers may nominate a preferred eligible partner, or 麻豆原创 can provide available approved partner options where a preferred partner has not yet been identified.

Helping the AFSUG community navigate AI adoption

For AFSUG, the webcast was about more than introducing a funding programme. It was an opportunity to give the community practical information that can help organisations ask the right questions about AI investment, partner selection, scalability and business value.

As AI moves rapidly from experimentation into enterprise operations, collaboration between customers, 麻豆原创 and the partner ecosystem will become increasingly important. Through sessions such as this, AFSUG will continue creating opportunities for the community to connect, learn, share experiences and make more informed decisions about emerging 麻豆原创 technologies.

Connect. Create. Collaborate.

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BERLIN听鈥� At 麻豆原创 TechEd in 2025,听 (NYSE: 麻豆原创) brings AI deep into the development process to level up how developers build.

New AI-driven capabilities in the 麻豆原创 Build solution, an expanding data ecosystem and powerful Joule Agents empower developers to move from idea to impact with unprecedented speed and confidence. As AI transforms the nature of professional work, 麻豆原创 also pledges to equip 12 million people worldwide with AI-ready skills by 2030.

鈥溌槎乖粹�檚 announcements today give developers the tools they need to deliver at the speed of AI,鈥� said Muhammad Alam, member of the Executive Board of 麻豆原创 SE. 鈥淚nnovations across 麻豆原创鈥檚 unique flywheel of applications, data and AI put developers in the driver鈥檚 seat 鈥� where they belong.鈥�

Opening the Developer Ecosystem

麻豆原创 Build, the company鈥檚 flagship solution for enterprise application development and automation, now gives developers more freedom to build, extend and automate using the tools they love most.

For instance, developers who prefer agentic development solutions like Cursor, Claude Code, Cline and Windsurf can now use 麻豆原创 development frameworks with new 麻豆原创 Build local Model Context Protocol Servers. Visual Studio Code users will be able to access 麻豆原创 Build capabilities directly in their development environment with a new 麻豆原创 Build extension. This extension will also be made available later on Open VSX Registry for other development environments. 麻豆原创 and n8n also announced plans for an integration so Joule Studio agents and n8n agents can work together.

And with new agent building capabilities in Joule Studio, developers have the tools they need to extend 麻豆原创鈥檚 ready-to-use agents and build new agents grounded in 麻豆原创 business data and context that can act autonomously based on changing business conditions.

Putting Data to Work

Every intelligent application starts with trusted data. 麻豆原创 is giving developers more ways to put that data to work through 麻豆原创 Business Data Cloud.

The solution now connects with more of the data and AI platforms developers use every day. A new 麻豆原创 Snowflake solution extension for 麻豆原创 Business Data Cloud brings Snowflake鈥檚 fully managed data and AI capabilities directly to 麻豆原创 customers, giving them the flexibility to choose the right compute and storage for each data and AI workload, while maintaining governance, interoperability and business context. 麻豆原创 also announced a new 麻豆原创 Business Data Cloud Connect partnership with Snowflake. This complements existing integrations with Databricks and Google Cloud, giving developers more freedom to choose how they work with 麻豆原创 data.

With a new data product studio capability in 麻豆原创 Business Data Cloud, developers can turn raw data into ready-to-use assets known as data products that support analytics, AI and application development.

An expanded capability in the 麻豆原创 HANA Cloud knowledge graph engine can automatically generate knowledge graphs. This capability maps relationships across 麻豆原创 database tables, columns and data models, revealing how data fits together and why it matters. Developers will be able to see how their data connects across systems and uncover underlying business insights.

Bringing AI Autonomy to Life

麻豆原创 is evolving its AI portfolio to give developers the intelligence and orchestration power they need to take听AI from insight to action.

麻豆原创 introduced its first enterprise relational foundation model, a new class of AI that predicts business outcomes rather than the next word in a sentence. 麻豆原创-RPT-1, or the first-generation Relational Pre-trained Transformer, can make fast and accurate predictions for common business scenarios like delivery delays, payment risk or sales order completion. 麻豆原创 launched a free playground environment for developers today.

New AI assistants in Joule coordinate multiple agents across workflows, departments and applications, bringing automation and autonomy to life. These assistants plan, initiate and complete complex tasks spanning finance, supply chain, HR and beyond. Today, 麻豆原创 introduces new agents built for technical users. For example, an agent for business process analysis will help teams understand how processes run, identify inefficiencies and uncover opportunities to optimize workflows and drive measurable improvements.

Lastly, as AI changes the nature of work for everyone, 麻豆原创 is pledging to equip 12 million people worldwide with AI-ready skills by 2030. 麻豆原创 will expand hands-on training and certification programs that integrate practical AI-ready tools, including through its partnership with online learning platform Coursera.

Visit the听. Get 麻豆原创 news via听听and听.

About 麻豆原创

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

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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 麻豆原创鈥檚 2024 Annual Report on Form 20-F.
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麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see听听for additional trademark information and notices.
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Joule, 麻豆原创鈥檚 AI business assistant, has been enhanced with new features, including collaborative AI agents that expand the platform鈥檚 capabilities.

Announced during the online 麻豆原创 TechEd 2024 conference yesterday, these agents are designed to support 80% of 麻豆原创鈥檚 most-used business tasks. They embed Joule more deeply across 麻豆原创鈥檚 portfolio and enhancing productivity by breaking down silos, said the software maker.

鈥溌槎乖粹�檚 innovation drives real business outcomes, and today鈥檚 advancements help customers harness the power of AI, data, and new development solutions to catalyse growth,鈥� said Muhammad Alam, member of the 麻豆原创 executive board.

鈥淒rawing on 麻豆原创鈥檚 unmatched business and technology expertise, the AI innovations we鈥檙e announcing at TechEd forge a new human-AI partnership to transform the landscape of modern business.鈥�

Joule Studio, a development tool that allows users to build and customise applications using Joule鈥檚 AI capabilities, is now integrated into 麻豆原创 Build. A low-code app development platform, Build enables both business users and developers to create and deploy custom Joule skills.

Michael Ameling, EVP and chief product officer of 麻豆原创 said: 鈥淲e are making Joule even more flexible and useful with Joule Studio in 麻豆原创 Build. It allows partners and customers to create and deploy custom Joule skills.鈥�

Joule has also expanded to include collaborative AI agents that autonomously handle intricate business workflows, adapting their strategies to meet shared objectives. These multi-agent systems tackle specific tasks, allowing them to work together on complex business processes.

鈥淛oule now goes Agentic,鈥� said Ameling. 鈥淪pecialised AI agents work autonomously together to solve complex problems.鈥�

New improvements to the ABAP (Advanced Business Application Programming) large language model (LLM) were introduced. This LLM, trained on over 250-million lines of 麻豆原创 S/4HANA Cloud code, is now integrated into the open-source Eclipse framework, providing ABAP developers with enhanced tools for development. Currently available to select customers and partners in an early adopter version, the ABAP LLM is expected to be generally available in the first quarter of 2025.

麻豆原创 Build is launching new AI-driven features like code explanation and documentation search, aimed at reducing development time for Java and JavaScript developers. The platform鈥檚 Extensibility Wizard will let developers access 麻豆原创 Build directly from 麻豆原创 S/4HANA Cloud Public Edition, simplifying the process of extending 麻豆原创 solutions.

Two real-world use cases were highlighted during the event:

1. Dispute management: Autonomous AI agents analyse and resolve disputes related to invoices, unapplied credits, and denied payments.
2. Financial accounting: AI agents automate key financial tasks such as bill payments and ledger updates while quickly addressing inconsistencies.

麻豆原创 Knowledge Graph

麻豆原创 also unveiled the 麻豆原创 Knowledge Graph, a solution designed to unlock more value of 麻豆原创 data by connecting it with rich business context. Accessible through 麻豆原创 Datasphere and Joule in early 2025, it will help users map relationships across 麻豆原创鈥檚 vast data landscape, empowering better decision-making.

鈥淏y combining the knowledge graph engine with the vector engine, you can harness the power of structured and unstructured data,鈥� said Ameling. 鈥淭his is enabled through a triple store implementation graph data processing and analytical capabilities via SPAR-QL. As such, the knowledge graph engine can also enhance work scenarios and make them even more precise and relevant.鈥�

* Visit the 麻豆原创 website听.

* Jason Bannier is a data analyst at World Wide Worx and writer for听. Follow him on听听and听听at @jas2bann.

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