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SNP advances its AI capabilities for unstructured data

  • Unstructured data represents around 80% of the enterprise data footprint and remains largely inaccessible to traditional transformation tools
  • SNP and New York based Structify establish joint venture company Oros Data LLC, focused on AI-enabled processing of unstructured data at scale
  • The new solution extends SNP's Kyano® platform to process unstructured data in M&A transactions, enabling faster time to value, reduced operational and compliance risk, and better-informed decisions
SINGAPORE - Media OutReach Newswire - 11 May 2026 - SNP SE, a leading provider of software for AI-enabled digital transformation, automated data migration, and data management in the SAP environment, has established a joint venture with Structify, a New York based AI-native Services-as- Software company that develops platform-based solutions for extracting, contextualizing, and processing enterprise data.

The new entity, Oros Data LLC, is jointly owned by the partners and focuses on the development and application of AI-based solutions for processing large volumes of unstructured enterprise data.

From left: Taichi Kato, Jens Amail (CEO SNP), Steele Arbeeny (CTO SNP NA), Alex Reichenbach (CEO Structify), Alex Goldstein, Dominik Wittenbeck (CTO SNP Group), Hovik Minasyan, Laura Garcia and Nico Marin Gamboa
From left: Taichi Kato, Jens Amail (CEO SNP), Steele Arbeeny (CTO SNP NA), Alex Reichenbach (CEO Structify), Alex Goldstein, Dominik Wittenbeck (CTO SNP Group), Hovik Minasyan, Laura Garcia and Nico Marin Gamboa

Together, SNP and Structify aim to bring AI-enabled data processing into the core of SAP transformation projects. According to industry analysts, unstructured data accounts for around 80% of enterprise information. This includes critical data such as contracts, sensitive HR records, IT-related documents, or customer complaints, which are often not readily accessible or processable. In the context of M&A transactions, insufficient handling of this data can create significant costs as well as operational and compliance risks for both buyers and sellers. In a first step, SNP integrates these capabilities into its Kyano platform particularly for M&A scenarios.

"Improper processing of unstructured data greatly increases the risks in M&A and can erode as much as 10% of the deal value. Customers have chosen SNP over the last 30 years to accelerate and de-risk their most critical transactions. We are excited to deliver this new AI-enabled capability based on our decades of experience to further streamline and safeguard our customers' M&A," says Steele Arbeeny, CTO of SNP North America.

"Unstructured data represents a significant share of the information required to run a business. Our goal is to make this data usable in M&A transactions while ensuring that sensitive information such as trade secrets and personal data is protected," comments Structify CEO Alex Reichenbach. "This collaboration provides a framework to apply these capabilities in large-scale transformation projects."

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The issuer is solely responsible for the content of this announcement.

About SNP

SNP (ticker: SHF.DE) is the global technology platform leader and trusted partner for companies seeking unparalleled data-enabled transformation capabilities and business agility. SNP's Kyano® platform integrates all necessary capabilities and partner offerings to provide a comprehensive software-based experience in data migration and management. Combined with the Bluefield® approach, Kyano sets a comprehensive industry standard for restructuring and modernizing enterprise data faster and more securely while harnessing AI-driven innovations based on over 30 years of experience.

The company works with more than 3,000 customers of all sizes and in all industries in over 80 countries, including numerous DAX 40 and Fortune 500 companies. The SNP Group has more than 1,600 employees worldwide at over 34 locations in 23 countries. The company is headquartered in Heidelberg, Germany, and generated revenues of around EUR 297 million in the 2025 fiscal year.

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