Nasuni has acquired DryvIQ as part of a strategy to expand its file data intelligence capabilities and help enterprises better understand the large volumes of unstructured information increasingly being used for artificial intelligence and broader data initiatives.
Nasuni Chief Product Officer Nick Burling framed the transaction around a fundamental enterprise data problem: organizations recognize that unstructured information can be one of their most valuable assets, but often lack sufficient visibility into what that data contains, while the cost and complexity of managing it continue to rise.
The acquisition is intended to strengthen Nasuni’s ability to help customers understand and manage file data before attempting to build broader data and AI strategies around it.
Nasuni’s own description of the transaction positions DryvIQ as an expansion of its file data intelligence capabilities for the AI era. The supplied material also indicates that the combination strengthens file synchronization and collaboration capabilities within Nasuni’s platform.
That combination addresses an increasingly important challenge for enterprises deploying AI against repositories containing documents, images and other unstructured files.
AI systems can only make effective use of enterprise information when organizations know what information they have, where it resides and how it should be managed. Improving visibility into file repositories can therefore become an important prerequisite for initiatives involving data governance, migration, collaboration and AI.
For Nasuni, integrating DryvIQ provides an opportunity to extend its role beyond the underlying management of enterprise file data toward helping organizations derive greater intelligence from those information assets.
Financial terms of the acquisition were not disclosed in the supplied material.
The transaction also reflects a broader shift in enterprise infrastructure as file storage increasingly intersects with data intelligence and AI readiness. Companies preparing large unstructured datasets for AI applications need technologies that can help identify and organize the information before those datasets can be governed or effectively used.
KEY QUOTE:
“Every enterprise I speak with tells me the same thing. They know their unstructured data is one of their most valuable assets, they know it’s one of their least understood, and the cost to manage it is spiraling.”
Nick Burling, Chief Product Officer Of Nasuni
