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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