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The Core of AI is Data 

Storage Architecture Determines the Success or Failure of Sovereign AI

Accusys, Dell and Seagate Come Together

A reliable sovereign data lake partner

What Is an AI Data Lake

An AI Data Lake is a centralized and horizontally scalable data storage architecture that retains massive volumes of structured, semi-structured, and unstructured data in its raw form. It can further transform this data into AI-ready vector databases, directly supporting AI development platforms and application models. Compared to traditional Data Warehouses, a Data Lake does not require predefined schemas (schema-on-read), allowing flexible ingestion and processing of diverse and dynamically generated data sources—including text, images, video clips, behavioral logs, and IoT sensor data. It also enables the transformation of raw data into AI-optimized intermediates
suitable for model training and inference.

[AI Data Lake is like a giant reservoir, storing every drop of data, later filtered and used for AI.]

What is a Sovereign AI Data Lake

A Sovereign AI Data Lake is a nationally planned, on-premise, locally governed core data infrastructure designed to securely store, manage, and utilize multi-source data generated within a specific country. It ensures that all data—ranging from sensitive government records and personal information to legal documents, medical records, educational content, cultural corpora, and industry datasets—remains secure, compliant, and within national borders.

[A Sovereign AI Data Lake is a secure national system that keeps all important data safe, organized, and within the country.]

Storage becomes the foundation of AI

In the data-driven era, storage is the foundation of AI—
the real competition is now about data.

Applications

Computing power

Storage

LLM, MoE, AI Agent, APP

Data Pool

Data Lake

Accusys Data Governance for the AI Data Lake

At the exabyte (EB) scale, traditional data management approaches fall short. To unlock the full value of massive, unstructured data sets, Accusys has developed an AI-driven data governance framework—purpose-built to transform raw data into actionable intelligence and ensure it is fully AI-ready.

This comprehensive framework goes beyond simple data preservation. It enables:

Automated data labeling

Intelligent data cleaning

Efficient data vectorization

These processes ensure that data is not only well-governed, but also AI-ready—fully optimized for training, fine-tuning, and deploying next-generation AI applications.

AI Data Lake Solution Diagram

AI Data Lake vs AI Data Pool

AI Data Lake

(Compliance & Preservation)

Definition: A long-term, centralized platform for AI data storage and governance.

Role: Ensures all AI source data can be collected, classified, cleaned, desensitized, vectorized, and preserved in full compliance with regulatory requirements.

Key Features:

  • Focus on security, compliance, and auditability.
  • Retains raw data without requiring prior formatting.
  • Supports structured, semi-structured, and unstructured data (e.g., video, images, IoT sensors).
  • Functions like a data reservoir, providing compliant “fuel” for AI.
 

AI Data Pool

(Computing & Creation)

Definition: A short-term, task-driven space for AI data computation and application.

Role: Draws data from the Data Lake to train AI models, run inference, and generate new content.

Key Features:

  • Prioritizes high-speed access and computing efficiency.
  • Optimized for model training, content creation, and rapid iteration.
  • Results can be reused and then returned to the Data Lake.
  • Functions like a working pond, enabling flexible, real-time AI innovation.
 

Our Workshops

  • Data Lake = Compliance Foundation → Ensures trustworthy, secure, and sustainable data.
  • Data Pool = Computing Stage → Transforms data into AI models, insights, and applications.
  • Cyclic Relationship → Data flows from Lake (preserve) → Pool (compute/use) → back to Lake (reuse), creating a continuous AI lifecycle loop.

[The AI Data Lake is the nation’s “data reservoir,” while the AI Data Pool is the “working pond” for AI computing — together, they enable trusted and efficient AI.]

The Life Cycle of AI Data

Infinite cycle growth

Three Facts Driving the Dramatic Growth of AI Data

Richer Content

The transformative potential of AI lies in multimodal AI models that ingest and produce multimedia material.

More Copies

As the model is training and producing output, the AI data is replicated countless times.

Longer Retention

Data preservation is the driving force behind the development of artificial intelligence and also helps to improve transparency.

Accusys

A leading high-performance storage technology company in Taiwan for 30 years, providing high-performance, modular, and scalable solutions

Seagate

Seagate is a global leader in data storage technology, focusing on developing high-capacity, high-performance hard drives and enterprise-class storage solutions.

Dell/EMC

Dell/EMC is a leading global provider of enterprise-class IT solutions, focusing on storage systems, servers, cloud infrastructure and data protection technologies.

Comprehensive Data Technology

Achieving a Sustainable Data Lake

EB-level Storage Data Management

Data controllability (Know where and what)

  • • Data Catalog, Metadata Management, Lifecycle Policy

Data integrity and compliance

  • • Access control and audit, data compliance

Data usability (Quick access and analysis)

  • • Access performance and data availability

Data value (Enables AI, decision-making, and innovation)

  • • Data quality and integrity
  • • Data annotation/labeling
  • • Data cleaning
  • • Data vectorization (AI-ready)

Why Choose Dell PowerScale as the

Core of AI Data Lake

A successful Data Lake hinges on two fundamental requirements: massive scalability and uncompromising security and compliance. These are precisely where Dell PowerScale excels.

As the world’s leading scale-out NAS and unstructured data platform, Dell PowerScale has been recognized as a Leader in the Gartner Magic Quadrant for nine consecutive years. Its proven reliability and performance have made it the platform of choice across mission-critical sectors—including defense, healthcare, scientific research, and AI-intensive industries.

With its unmatched scalability, integrated cybersecurity features, and AI-optimized architecture, Dell PowerScale provides the ideal foundation for a sovereign-grade, AI- ready Data Lake infrastructure.

Five Key Advantages of Dell PowerScale as the Core Storage Architecture for AI Data Lake:

Exabyte-Scale Modular Design

Dell PowerScale features a truly modular, scale-out architecture that supports seamless horizontal expansion—from terabytes (TB) to zettabytes (ZB). This capability aligns perfectly with the AI Data Lake’s 50-year data growth projection of 15% CAGR, ensuring future-proof scalability.

AI-Native Performance

Purpose-built for AI and machine learning, PowerScale delivers high-throughput, low-latency access with native support for parallel file systems. It enables real- time data ingestion, pre-processing, and model training across AI-ready workloads.

Advanced Data Services

PowerScale offers a rich set of integrated data services, including SnapshotIQ, SmartTier hierarchical storage, WORM compliance, and hybrid cloud integration. These capabilities empower robust data governance, lifecycle management, and multi-workload optimization.

Security and Compliance Assurance

Equipped with FIPS-certified encryption, role-based access control (RBAC), end-to-end audit trails, and immutable data protection, Dell PowerScale ensures strict compliance with industry-specific regulations including the Personal Data Protection Act and the forthcoming AI Basic Law—providing a secure and accountable foundation for data management across healthcare, finance, manufacturing, and other regulated industries.

Low Total Cost of Ownership (TCO) with Global Support

Designed for high-density, energy-efficient deployments, PowerScale leverages Dell’s global supply chain and service ecosystem to reduce long-term operational costs and risks—delivering sustainability, reliability, and peace of mind for national- scale infrastructure.

Extreme Scalability

When designing a Sovereign AI Data Lake, extreme scalability is the foremost architectural requirement.

With the rise of generative AI, IoT, digital government, and smart society initiatives, data volumes are expanding at an explosive pace, growing by over 15% compound annual growth rate (CAGR). This implies that within 50 years, total data volume may scale from today’s petabyte level to zettabyte scale or even beyond.

Dell PowerScale’s modular, scale-out architecture enables the data lake to grow incrementally based on demand, avoiding large upfront investments. This approach reduces deployment risk and optimizes long-term total cost of ownership (TCO), making it an ideal foundation for scalable and future-proof national data infrastructure.

Scalable and Upgradable: Dell PowerScale

Automatic data balancing

Painless iteration and upgrade/replacement

Linear scale-out architecture

A minimum of 3 nodes and a maximum of 252 nodes meet large-scale data storage needs

A single namespace can scale up to 186PB of raw capacity

Native host connection interface support:

Dual 10/25GE port supports NFS, SMB, HDFS, S3, REST, HTTP, NDMP, and FTP

Extreme Security and Compliance

For a national-scale data lake, security and compliance are not optional features— they are the foundation of trust and sustainable operation. As the platform consolidates sensitive government records, personal data, medical files, legal documents, educational resources, and industrial datasets, even a single breach could trigger severe national and societal risks.

A Sovereign AI Data Lake must therefore meet the highest standards of cybersecurity and regulatory compliance. There is no sovereignty without security, and no path to sustainability without compliance. To achieve this, the system requires a fully auditable, verifiable, and trustworthy end-to-end defense and governance framework— extending from infrastructure to operational policies.

Security Compliance: Dell PowerScale

PowerScale offers the industry’s most advanced data protection and security defenses.

Compliant with U.S. defense standards – a national security architecture.

  • Multi-factor authentication
  • Support for external SED key storage
  • Utilizes the Federal STIG Profile to enhance overall cluster system security
  • Secure Boot ensures only authorized firmware or OneFS is loaded (ensuring virus-free operation)

PowerScale for AI Training / Inference

PowerScale Supports GPU Direct

PowerScale supports GPUDirect and provides GPU performance analysis.

  • Provides NFS over RDMA for faster, more secure, and low-latency data access.
  • Reduces I/O latency between the AI host and storage, reducing AI host CPU load.
  • Provides NVIDIA GPUDirect Protocol functionality.
 

Seagate Corvault for AI Training / Inference

Intelligent Massive Block-Level Storage Device

This HDD-based computing storage solution is only 1/5 the cost of SSD architecture, offering excellent performance and capacity at an exceptional price-performance ratio!

  • Fast Rebuild: Next-Generation ADAPT RAID

  • Self-repair: ADR Technology

  • Density: 2.5PB storage space in a 4U chassis

  • Performance: 14GB/s, 12GB/s R/W, 17,680 IOPS

  • Availability: “Five Nines” – 99.999%

  • Efficient: Ultra-large-scale architecture

  • Protection: Seagate Secure® built-in.

 

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