Huawei unveils full-stack data infrastructure for AI data centers

Huawei unveiled a full-stack data infrastructure solution for AI data centers at its IDI Forum 2026. The new architecture aims to accelerate large-scale AI adoption for enterprises by targeting core pillars like data storage, compute, and models.

Huawei unveiled a full-stack data infrastructure solution for artificial intelligence data centers (AI DCs) to accelerate construction and large-scale AI adoption for enterprises. Yuan Yuan, Vice President of Huawei and President of the Huawei Data Storage Product Line, announced the framework during a keynote speech at the Huawei Innovative Data Infrastructure (IDI) Forum 2026 held on May 21.

Targeting Core Operational Pillars

According to the company, AI agents are transforming enterprise operations and evolving into "digital employees." To support this shift, the newly introduced architecture systematically targets several core operational pillars, which include data lakes, AI data platforms, compute power, models, agent frameworks, and data resilience.

High-Density Storage and Unified Data

As per Huawei, the infrastructure utilizes high-density OceanStor Pacific Scale-Out Storage to deliver 11 PB capacity in a 2 U space for massive data storage. This is paired with DME Omni-Dataverse, a unified data space solution that supports multimodal, cross-site, and real-time data import alongside global data visibility.

Accelerating Ultra-Scale Inference

For ultra-scale inference clusters, the company introduced a Context Memory Storage (CMS) supporting heterogeneous computing power. This system expands into a PB-scale shared KV cache pool, which reduces the time to first token (TTFT) by 90 per cent.

Enhancing Enterprise Inference Scenarios

For enterprise inference scenarios, the framework integrates an AI data platform combining KV cache acceleration, a knowledge base with over 95 per cent retrieval accuracy, and an evolving memory bank. Managed by a Unified Cache Manager (UCM), the integration improves inference accuracy by 30 per cent.

Simplified Model and Agent Development

According to the company, a dedicated ModelEngine provides model gateway capabilities for zero-code adaptation and one-click deployment. Through fine-grained compute resource partitioning, it achieves an up to 1:10 ratio of xPU partitioning, allowing one xPU to serve multiple purposes. Development is further supported by the ModelEngine Nexent agent platform, which generates agents through natural language-based interaction, reducing rollout time by 80 per cent.

Comprehensive Data Resilience

The full-stack solution also incorporates a data resilience platform designed to prevent tool misuse, data poisoning, tampering, and ransomware attacks across agents, models, and infrastructure.

Future Outlook and Industry Collaboration

Yuan emphasized the critical role of data asset protection and industrial collaboration during the presentation. "AI is unlocking new opportunities for the IT industry," Yuan said. "The next chapter of AI is data. Committed to technological innovation in data storage, Huawei will accumulate the experience of industrial AI adoption, and work closely with the entire industry to help customers accelerate their journey into the intelligent era." (ANI)

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