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Everpure Debuts New Data Management Tools for Enterprise AI

Everpure Debuts New Data Management Tools for Enterprise AI

London-based data storage firm Everpure is rolling out a suite of platform upgrades designed to bridge the gap between static enterprise data and real-time AI performance. By automating data governance and optimizing inference costs, the company aims to help organizations transition autonomous AI agents from experimental pilots into active production environments.

The updates, arriving this October, address the friction between existing data architecture and the requirements of autonomous agents. Prakash Darji, General Manager of Data & Digital Experience at Everpure, noted that enterprise AI often stalls not due to model limitations, but because data remains unprepared for real-time interaction. The new tools integrate the open Model Context Protocol (MCP), allowing AI agents to query live data catalogs through natural language without requiring custom API development.

Performance enhancements target the hardware-software bottleneck directly. The introduction of PureKVA (Key-Value Accelerator) for FlashBlade systems pre-stages context into GPU memory, claiming a 20x improvement in Time to First Token. Alongside this, the platform introduces DeepReduce, a compression engine that identifies sub-block similarities to expand usable storage capacity automatically. These features are designed to function without data relocation, keeping information secure within its primary system of record while lowering the overall costs associated with external API token usage.

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