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The Storage Wall: Why AI Is Breaking on Data, Not Compute
As inference workloads outpace compute growth, the constraint that decides whether AI projects succeed is no longer how much an enterprise can process, but whether it can control, trust and serve the data underneath. Two of the storage industry’s senior regional voices describe a shift that has moved storage from afterthought to foundation.
DataVolt secures up to $150m to build one of Central Asia’s largest AI-ready data centres in Uzbekistan
Four development finance institutions have backed the 12MW Tashkent facility on non-recourse terms, a structure that signals confidence in Uzbekistan’s digital infrastructure market and its push to grow AI products and services to $1.5bn by 2030.
Everpure bets its roadmap on data primacy, sequencing every release around one path to production AI
At Accelerate 2026, the company unified Data Intelligence, Data Stream, and its Enterprise Data Cloud updates behind a single argument: that enterprises must treat data, not applications, as their system of record before AI can be trusted in production.
Confluent Moves to Close the Gap Where Enterprise AI Projects Quietly Die
The data streaming pioneer has shipped a wave of capabilities aimed at the security and engineering failures that stall most AI deployments before they reach a single customer, with Steve Fernandes arguing that real-time data has become the precondition the market can no longer treat as optional.