One Data launches AI-native platform version for Trusted Data in the enterprise

Passau, May 5, 2026 – One Data today introduces the new version of its platform, which uses AI agents to automate core data processes, support SAP BW migrations and transform fragmented enterprise data into trusted data products. This enables companies to build and operate data products up to 60 percent faster, accelerate data searches by up to 70 percent and reduce coordination efforts between business units and data teams by up to 50 percent.

While companies are investing heavily in AI, the underlying data foundation often remains the critical bottleneck. Fragmented data landscapes, unclear business logic, lengthy coordination processes and established legacy systems prevent AI applications from scaling reliably across the enterprise. With the new version, One Data addresses precisely this challenge: the platform helps companies make data available not only in a technical sense, but also in a way that is transparent, quality-assured and aligned with business requirements.

“The bottleneck today is often not the AI model, but the data beneath it. If this data is not trusted, not aligned or trapped in silos, AI primarily scales poor decision-making. Trusted Data is therefore the prerequisite for AI to reliably create value in the enterprise,” says Dr. Andreas Böhm, founder and CEO of One Data.

Achim Berg, Chairman of the Advisory Board at One Data, also places the launch in a broader enterprise context: “AI is not a shortcut to better decisions, but a stress test for an organization’s data maturity. It reveals which weaknesses in data landscapes have been tolerated for years. Anyone who wants scalable AI needs scalable trust in their data. Without that trust, AI remains stuck in demo mode.”

From manual data processes to AI-powered automation

The new version represents a fundamental advancement in how companies work with enterprise data: moving away from manual, coordination-intensive processes toward intelligently automated workflows for building, operating and using data. The platform supports key steps in the data process with AI: from analyzing existing data sources and defining business requirements to quality checks, data contracts, documentation and lifecycle management. As a result, business users, analysts and consultants can increasingly create data products independently, without having to rely continuously on data teams or data engineers.

For companies, this creates a direct productivity gain. Data products can be built within minutes, secured through standardized data contracts and managed automatically throughout their lifecycle. At the same time, data teams are relieved of repetitive tasks and can focus more strongly on complex architecture, governance and scaling topics.

“The new version marks our transition to a fully AI-native product. Many functionalities are now delivered through AI agents. This creates a much broader automation portfolio that enables customers to automate more processes faster and more reliably,” says Böhm.

Trusted Data as the foundation for AI agents

A key aspect of the new version is Trusted Data as a prerequisite for the reliable use of AI agents. AI agents can only deliver robust results when they access verified, transparent and business-aligned data. To enable this, the platform combines metadata management, data contracts, automated quality checks, data lineage and AI-powered automation in a single platform. This gives companies greater transparency across their data landscape, enables them to find data sources and data products faster and helps them automatically identify quality risks.

The business impact is measurable: depending on the use case and starting point, companies can reduce the time required to build and maintain data products by up to 60 percent, lower manual data engineering effort by up to 50 percent and accelerate data search across the organization by up to 70 percent.

“The most important innovation is not a single feature, but the way everything works together: Trusted Data is created through the combination of metadata management, AI automation, usability and quality assurance. This combination is the hero feature of our new version,” says Böhm.

Making SAP BW migrations faster and more transparent

A particular focus of the new version is SAP BW migrations. Many companies face the challenge of replacing established BW systems without losing key financial metrics, planning logic, reports or business logic. In many cases, however, it is no longer transparent how this logic was created, where it is used or how it can be transferred into modern target architectures.

The new version supports companies in automatically analyzing legacy code, translating it with a high level of quality and migrating it into target systems. At the same time, business documentation is created and kept up to date automatically. This not only accelerates SAP BW migrations, but also makes them more transparent and more robust from a business perspective.

Automation reduces manual effort, lowers the risk of knowledge loss and creates a modern data foundation for reporting, planning, management and AI applications.

Self-service data for business units

In addition to migration and automation, the new version also improves the user experience for business units. Users can create, review and further develop data products more easily. This includes self-service data pipelines, AI-powered code execution and improvement, as well as the ability to define business-specific quality requirements directly.

Examples include expected value ranges, mandatory fields, plausibility checks or business validation rules. These requirements are monitored automatically and secured through data contracts. Business units gain more room to act, while governance, quality and transparency are maintained.

The result: companies can respond more quickly to urgent business questions, provide decision-relevant information earlier and implement data-driven use cases with less infrastructure and coordination effort. With the new version, One Data is evolving its platform from classic enterprise data management into an AI-native solution for Trusted Data, creating the foundation for analytics, automation and AI to move beyond pilots and operate at scale in the enterprise.