Storage and data management company Everpure has unveiled a new data-primacy architecture designed to help organisations accelerate AI initiatives while maintaining visibility, governance, and control over enterprise data.
The Everpure Data Intelligence, formerly known as 1touch.io, and updates to the Enterprise Data Cloud (EDC) platform aim to transform fragmented enterprise data into trusted, AI-ready intelligence.
“AI completely upends the traditional IT hierarchy; enterprises that do not shift from app-centricity to data primacy will fall behind. Because data is a company’s primary asset, embedding context, semantics and governance directly at the data layer is the right way to reduce data fragmentation created by the growth of apps and AI agents. Enterprises need to consolidate their fragmented enterprise data footprint into a real-time corpus of trusted intelligence,” said Charles Giancarlo, CEO of Everpure.
Accelerating enterprise AI adoption
Data Intelligence delivers three core capabilities:
- Universal Discovery: Offers visibility into structured and unstructured data regardless of storage format
- Automated Governance: Automatically scans the entire system to identify sensitive info (like PII and PHI) and track lineage
- AI-Ready Context: Maps raw data directly to its real-world business definition, creating a semantics knowledge graph.
The solution works across the Everpure platform, public cloud services, SaaS applications, and third-party storage systems.
Matt Kimball, VP & Principal Analyst, Moor Insights & Strategy, said: “The biggest bottleneck to AI adoption right now isn’t the software, it’s the plumbing. Putting data at the absolute centre of the enterprise strategy is exactly how IT leaders can rein in runaway operational costs and accelerate rollouts.”
The company also announced enhancements to its Enterprise Data Cloud architecture, including updates to its Unified Data Plane and Intelligent Control Plane.
To support adoption, Everpure introduced the EDC Success Blueprint, a roadmap that helps organisations transition from traditional infrastructure management to a highly automated, data-centric operating model.
