Nasuni Adds Governed AI Access to File Data Platform After DryvIQ and Resilio Deals

Blocks & Files reported that Nasuni has expanded its Operational File Data Platform for the AI era with content intelligence, governance, file synchronization and edge acceleration capabilities, while introducing a PSYCHIC framework for what it calls AI-ready data.

The update turns two acquisitions from earlier this year into generally available product functions.

DryvIQ, bought in August, supplies content intelligence and governance for Nasuni's file data platform.

Resilio, bought in April, adds high-performance file synchronization and edge acceleration.

Together they push Nasuni beyond its older cloud file services and collaboration position toward an unstructured data platform meant to let enterprise workers and AI systems use the same current file estate.

The platform is organized around a single global namespace that can manage, protect and activate unstructured data at scale.

Nasuni chief executive Sam King framed the release as a response to a gap between broad LLM adoption and measurable business value, citing rising token costs, limited production-scale deployments and governance programs that have not kept pace.

Her central claim was that enterprise advantage sits less in the model itself than in proprietary data, business context and enterprise intelligence.

DryvIQ gives the platform a governance layer spanning enterprise content stores such as Microsoft 365, Google Drive, Box, Amazon S3 and local NAS systems, with more than 40 repositories covered overall.

It can sort material in 550 file formats and 75 languages, flag PII, PHI and PCI records, and process hundreds of terabytes each day.

Enterprises can use those classifications to separate valuable, risky, redundant, obsolete or trivial material and apply automated policies across the estate.

The AI access layer uses AI Activate to put third-party MCP-compatible AI platforms and agents in contact with enterprise file stores via the open Model Context Protocol.

A metadata and content index powers the connection, but existing permissions are checked before any content is exposed.

That design is meant to let agents work from live operational files rather than a curated copy built outside the main file environment.

Nasuni also added hosted, permission-aware full-text enterprise search across the operational file environment, with availability described as coming soon.

Resilio 6.0 moves delivery to edge locations with peer-to-peer distribution on commodity hardware, reaching as much as 200 Gbps without a VPN, dedicated infrastructure or caching appliances.

The source cited construction sites, studios, field offices and survey vessels as examples of locations where staff can use globally governed files with local responsiveness.

McKim and Creed was described as retiring 27 file servers into Nasuni, while remote engineers in early Resilio trials reported a 50% productivity gain.

Chief product officer Nick Burling tied the architecture to sovereignty and security requirements.

He highlighted a mix of global namespace design, immutable versioning, built-in permission controls and customer-owned object storage as a way to meet residency rules without splitting environments into regional silos.

The same controls would also reduce the need for security teams to approve a new data pipeline each time the business adopts an AI tool.

The PSYCHIC framework defines Nasuni's checklist for AI-ready file data: proprietary, secure, yours, current, hybrid, indexed and continuous.

The broader market pressure is similar across Box, CTERA, Egnyte, Nasuni and Panzura, which are all trying to expose governed file data to AI models and agents through content intelligence, permissions and MCP-style access.

That condition leaves cloud file services, edge storage and distributed data management suppliers competing over who controls the governed path between enterprise files and AI systems.