{"id":11098,"date":"2026-11-02T15:48:36","date_gmt":"2026-11-02T15:48:36","guid":{"rendered":"https:\/\/www.dab-europe.com\/?post_type=articles&p=11098"},"modified":"2026-11-03T07:46:12","modified_gmt":"2026-11-03T07:46:12","slug":"new-partnership-neuland-ai-and-dab-combine-sap-data-expertise-with-sovereign-ai-orchestration","status":"publish","type":"articles","link":"https:\/\/www.dab-europe.com\/en\/articles\/new-partnership-neuland-ai-and-dab-combine-sap-data-expertise-with-sovereign-ai-orchestration\/","title":{"rendered":"New partnership: neuland.ai and dab combine SAP data expertise with sovereign AI orchestration"},"content":{"rendered":"\n
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AI applications deliver the greatest value when they can access relevant business data and processes. SAP systems contain a wealth of valuable information from finance, procurement, production, HR and many other business functions.<\/p>\n\n\n\n

However, SAP data is complex. It is distributed across numerous tables, follows specific process logic and is often configured to meet individual customer requirements. Simply giving AI access to this raw data is therefore not enough. To deliver meaningful analysis, the data must be accessed reliably, structured from a business perspective and made understandable within its wider context.<\/p>\n\n\n\n

This is precisely where the technology partnership between neuland.ai and dab<\/a> comes in. With the neuland.ai HUB, neuland.ai provides the central platform for orchestrating and managing AI across the enterprise and integrating it into business processes. dab provides access to the SAP data landscape and prepares the required data for use in AI-powered workflows.<\/p>\n\n\n\n

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The neuland.ai HUB as a central platform for Enterprise AI<\/h2>\n\n\n\n

The neuland.ai HUB<\/a> provides the central management and orchestration layer for using AI across the enterprise. The platform enables organisations to centrally manage different AI models, agents and workflows, connect them to enterprise data in a controlled manner and integrate them into existing business processes.<\/p>\n\n\n\n

This goes far beyond a conventional chat interface for enterprise data. AI agents can independently complete tasks, identify relevant data sources, analyse information and provide results in the form of answers, reports or visualisations.<\/p>\n\n\n\n

The ontology approach within the neuland.ai HUB plays an important role in this process. It makes information about available data and its business relationships accessible to AI agents. This allows agents to select data sources more precisely and process information within the relevant business context.<\/p>\n\n\n\n

To extend these capabilities to SAP-based business processes, organisations need a reliable and contextually structured data foundation. This is where dab complements the technology of the neuland.ai HUB.<\/p>\n\n\n\n

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dab connects the neuland.ai HUB to the SAP data landscape<\/h2>\n\n\n\n

SAP systems contain business-critical information, but they do not automatically provide it in a form that AI agents can process effectively. Different data structures, complex relationships and SAP-specific logic require targeted preparation.<\/p>\n\n\n\n

This is precisely the role that dab performs. Using a certified, Clean Core-compliant approach<\/a>, dab provides access to the relevant SAP data and transforms technical structures into business-ready data models.<\/p>\n\n\n\n

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The architecture diagram shows how dab accesses and provides SAP raw data, transforms it into contextually structured main and sub-data products, and makes it available in the neuland.ai HUB for use by the ontology, AI agents and AI-powered applications.<\/figcaption><\/figure>\n\n\n\n
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This results in semantically enriched data products<\/a> for areas such as accounts payable, accounts receivable, procurement and HR. Within the neuland.ai HUB, the prepared SAP data can then be combined with information from other connected enterprise sources, such as CRM systems or emails.<\/p>\n\n\n\n

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How the technologies from neuland.ai and dab work together<\/h2>\n\n\n\n
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  1. 1. Access SAP data<\/strong>
    dab establishes the connection to the relevant SAP systems and extracts the data required for the specific use case.
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  2. 2. Structure SAP data within its business context<\/strong>
    The extracted raw data is transformed into semantically enriched data products, taking SAP structures, data relationships and business logic into account. <\/li>\n\n\n\n
  3. 3. Make SAP data available to the neuland.ai HUB<\/strong>
    The structured main and sub-data products are then made available in the neuland.ai HUB as the underlying data foundation.
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  4. 4. Make context accessible within the HUB<\/strong>
    The ontology approach of the neuland.ai HUB makes available information and the relationships between it accessible to AI agents. This enables agents to identify which data is relevant to a particular question.
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  5. 5. Support business processes with AI agents<\/strong>
    On this basis, AI agents can analyse data, examine relationships and provide results in the form of answers, reports or visualisations. The key difference is that users are no longer limited to predefined reports. Instead, they can interact directly with their SAP data, explore new questions flexibly and investigate specific points in greater detail.<\/li>\n<\/ol>\n\n\n\n
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    AI agents and SAP data in practice<\/h2>\n\n\n\n

    neuland.ai and dab demonstrated how this approach works in practice during a joint AI Colloquium<\/a> (German only). An agent within the neuland.ai HUB accessed SAP data provided by dab and analysed procurement data, accounts payable data and open items.<\/p>\n\n\n\n

    This data foundation enables users to ask specific questions about their enterprise data. AI can identify patterns and anomalies and present the results in natural language. Potential questions include:<\/p>\n\n\n\n