SNP & Structify launch Oros Data venture for M&A files

SNP and Structify have formed a joint venture, Oros Data, to process unstructured enterprise data for M&A transactions.

The new business is jointly owned and extends SNP's Kyano platform into an area the partners say has been poorly served by traditional transformation tools.

Unstructured data includes contracts, HR records, IT documents and customer complaints. This type of information accounts for about 80% of enterprise data, according to the companies, yet often remains difficult to access and analyse during corporate transactions.

That is a particular challenge in dealmaking, where buyers and sellers must review, transfer and govern large volumes of information quickly. Poor handling of those records can increase operational risk, create compliance problems and weaken decision-making during integrations and carve-outs.

Deal focus

Oros Data has been set up to develop and apply AI-based tools that can process large volumes of unstructured enterprise information. In its first phase, the work will target M&A situations through SNP's existing platform.

SNP is known for software used in SAP-related data migration and transformation projects. By adding Structify, a New York-based company that builds software to extract and process enterprise data, the group aims to broaden the range of information that can be handled in those projects.

The move reflects a broader market shift as companies try to use AI to manage messy data sources outside structured databases. While financial and operational systems have long been central to due diligence and integration planning, text-heavy files, document archives and other informal records have often required manual review.

That can slow transactions and raise costs, especially in larger cross-border deals where sensitive information must be identified and controlled. It also makes it harder to separate data sets cleanly when a business unit is sold or merged.

SNP said the financial impact can be significant, pointing to the risk that poor handling of unstructured data can damage deal value in M&A processes.

"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," said Steele Arbeeny, Chief Technology Officer, SNP North America.

Data access

Structify positioned the venture as a way to make neglected information usable without exposing sensitive material. That is a central concern in transactions involving trade secrets, employee records and customer data, where access controls and disclosure rules can affect both timetable and outcome.

"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," said Alex Reichenbach, Chief Executive Officer, Structify.

"This collaboration provides a framework to apply these capabilities in large-scale transformation projects," he added.

The joint venture also highlights how software providers are tying AI tools more closely to core corporate processes rather than treating them as separate analytics products. Here, the focus is on using those tools in transaction and transformation work, where delays or errors can have direct financial consequences.

SNP works with more than 3,000 customers in over 80 countries and generated about EUR 297 million in revenue in its 2025 financial year. The Heidelberg-based company has more than 1,600 employees across 23 countries.

For Structify, the tie-up offers a route into larger transformation programmes involving SAP environments and complex business separations. For SNP, it adds specialist capability around documents and other non-tabular information that has become harder to ignore as companies face tighter scrutiny over governance, privacy and post-deal execution.

The venture comes as corporate buyers face pressure to complete integrations faster while keeping tighter control over data flows. In that environment, the ability to identify what sits in unstructured files, assess its relevance, and move or protect it correctly has become a more visible part of transaction planning.

Oros Data will be the vehicle for that effort, with initial work focused on giving SNP's M&A customers a way to process information that has typically sat outside standard migration workflows.