Huawei Powers 3,900+ Hospitals with AI Storage

Huawei has announced that its data storage infrastructure now supports more than 3,900 healthcare facilities. These institutions have successfully upgraded from basic digital records to advanced intelligent systems.

This milestone was revealed by Wu Junjie, Vice President of Huawei's Data Storage Product Line. He spoke at the 2026 Huawei Global Education and Healthcare Partner China Week event.

The company emphasizes that healthcare is undergoing one of the fastest智能化 (intelligent) transformations among all industries globally.

Key Facts

• Scale: Over 3,900 medical institutions utilize Huawei storage for smart upgrades.
• Technology: Shift from single-model assistance to multi-modal large model clinical support.
• Performance: OceanStor Dorado delivers 100 million IOPS with 0.03ms latency.
• Cost Efficiency: New solutions significantly reduce hardware deployment and maintenance costs.
• Availability: Core business systems maintain 7x24 hour uptime via gateway-free active-active setups.
• Solutions: Four major solution categories launched to solidify the digital-intelligent foundation.

The Shift to Multi-Modal AI in Healthcare

Medical artificial intelligence is accelerating its iteration cycles rapidly. Earlier applications focused on simple tasks like triage guidance or medical record quality checks. These were limited to single-model auxiliary functions.

Now, the industry is evolving toward comprehensive clinical decision support. This new phase relies on multi-modal large models that can process diverse data types simultaneously. Such systems analyze images, text, and patient history together for better diagnostics.

Huawei positions its storage infrastructure as the critical backbone for this evolution. Without robust data handling capabilities, complex AI models cannot function effectively in real-time hospital environments.

The demand for speed and reliability is paramount in healthcare. A delay in accessing patient data can impact critical care decisions. Huawei addresses this by integrating high-performance storage directly with AI workflows.

Core Business Data Fusion Strategy

Huawei introduced a core business data fusion solution designed specifically for hospital needs. This system integrates OceanStor Dorado all-flash storage with DCS virtualization software.

It also includes the DME management platform for unified oversight. A single storage device now provides SAN, NAS, and S3 protocols simultaneously. This convergence simplifies the infrastructure required for Hospital Information Systems (HIS) and Picture Archiving and Communication Systems (PACS).

Reducing Complexity and Cost

Traditional setups often require separate hardware for different protocol needs. Huawei’s approach eliminates this redundancy. It significantly reduces both hardware deployment complexity and ongoing operational maintenance costs.

Hospitals can manage their entire data lifecycle through one streamlined interface. This efficiency allows IT teams to focus on innovation rather than troubleshooting legacy hardware conflicts.

The solution ensures seamless integration with existing medical workflows. It does not require disruptive changes to established hospital procedures during the upgrade process.

High Performance for Peak Loads

Healthcare facilities experience significant traffic spikes during peak hours. Emergency rooms and outpatient clinics generate massive amounts of data instantly. Traditional storage systems often struggle under this sudden load.

Huawei’s solution offers multi-protocol gateway-free active-active capabilities. This architecture guarantees 7x24 hour uninterrupted service for core business operations. There is no single point of failure in this setup.

Speed Metrics Matter

The system delivers up to 100 million IOPS (Input/Output Operations Per Second). Latency is reduced to an ultra-low 0.03 milliseconds. These metrics are crucial for preventing system lag during busy periods.

Doctors no longer wait for imaging files to load. Patient records appear instantly on screens. This responsiveness improves the overall patient experience and clinical efficiency.

Compared to older spinning disk arrays, the performance gap is substantial. All-flash technology provides the necessary throughput for modern AI-driven diagnostic tools.

AI Data Lake and Total Cost of Ownership

For long-term data retention and analysis, Huawei deployed the AI Data Lake solution. This uses OceanStor Pacific all-flash distributed storage technology.

The system achieves industry-leading high-capacity density. It optimizes the Total Cost of Ownership (TCO) for storing vast amounts of medical data. Hospitals retain years of historical records without prohibitive expenses.

DME Omni plays a key role in managing this data lake. It ensures data is accessible and organized for AI training purposes. Large models require clean, structured data to perform accurately.

By centralizing data storage, hospitals can leverage their archives for research. This turns passive data storage into an active asset for medical discovery and improved patient outcomes.

Industry Context and Global Implications

The global healthcare sector is investing heavily in digital transformation. Western markets, including the US and Europe, face similar challenges with legacy infrastructure.

Huawei’s progress highlights a broader trend: storage is becoming an AI enabler. It is no longer just about saving files but about feeding intelligent algorithms in real time.

Competitors like Dell and HPE are also focusing on AI-ready storage. However, Huawei’s rapid adoption in Asia demonstrates the scalability of their all-flash approach. This success may influence procurement strategies in other regions.

Regulatory compliance remains a critical factor. Medical data requires strict security and privacy protections. Huawei’s integrated management platforms aim to address these concerns through built-in governance features.

What This Means for Healthcare Providers

Hospital administrators must prioritize infrastructure that supports AI growth. Investing in siloed storage systems will soon become obsolete.

Providers should evaluate vendors based on protocol convergence and latency metrics. The ability to handle multiple data types simultaneously is non-negotiable for modern clinics.

Furthermore, the shift to multi-modal AI requires robust data lakes. Institutions need to plan for scalable storage that grows with their AI ambitions. Ignoring this step will hinder future diagnostic capabilities.

Looking Ahead

The integration of AI in healthcare will only deepen. Future developments may include predictive analytics for population health management.

Huawei plans to expand its partner ecosystem further. More specialized medical software vendors will likely integrate with these storage solutions.

As 5G and edge computing mature, remote diagnostics will rely on this infrastructure. The foundation laid today will support tomorrow’s telemedicine breakthroughs.

Gogo's Take

• 🔥 Why This Matters: This isn't just about faster servers; it's about enabling life-saving AI diagnostics. By reducing latency to 0.03ms, doctors get instant access to critical data, potentially improving survival rates in emergency scenarios where seconds count.
• ⚠️ Limitations & Risks: Dependence on a single vendor for such critical infrastructure creates supply chain risks. Additionally, while TCO is optimized, the upfront cost of all-flash arrays remains high compared to traditional hybrid setups, posing a barrier for smaller clinics.
• 💡 Actionable Advice: Healthcare CTOs should audit their current storage protocols. If you are still using separate systems for PACS and HIS, begin planning a migration to converged all-flash architectures to prepare for multi-modal AI integration within the next 12-18 months.