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.

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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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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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