Tackling the Global "Compute Shortage": 3 E Network Technology Unveils a Next-Gen AI Data Center Solution

Rhea-AI Summary

3 E Network Technology (Nasdaq: MASK) announced the core technical architecture for a high-performance AI data center after signing a land lease in Mikkeli, Finland (Dec 2025). The modular, prefabricated design targets rapid "plug-and-play" deployment versus typical 18+ month builds. Key specs include 20kW+ rack power density, support for liquid-cooled racks, InfiniBand/RoCE low-latency interconnects, and an AI-driven operations stack. The company expects an 8%–15% annual PUE reduction via smart cooling and claims predictive maintenance, dynamic power scheduling, and AI security to improve availability and reduce O&M costs.

Positive

• Land lease signed in Mikkeli, Finland (Dec 2025)
• 20kW+ rack power density for AI workloads
• Modular prefabricated design shortens deployment time
• 8%–15% expected annual PUE reduction via smart cooling

Negative

• High AI chip power (>700W) increases infrastructure energy demand
• Support for 20kW+ liquid-cooled racks implies significant capex

News Market Reaction

-17.96%

17 alerts

-17.96% News Effect

+29.2% Peak Tracked

-17.9% Trough Tracked

-$2M Valuation Impact

$8M Market Cap

0.8x Rel. Volume

On the day this news was published, MASK declined 17.96%, reflecting a significant negative market reaction. Argus tracked a peak move of +29.2% during that session. Argus tracked a trough of -17.9% from its starting point during tracking. Our momentum scanner triggered 17 alerts that day, indicating notable trading interest and price volatility. This price movement removed approximately $2M from the company's valuation, bringing the market cap to $8M at that time.

Data tracked by StockTitan Argus on the day of publication.

Key Figures

2025 Revenue: US$4,835,167 Convertible note offering: US$2.0 million AI data center capacity: 26MW +5 more

8 metrics

2025 Revenue US$4,835,167 Fiscal year ended June 30, 2025 (Form 20-F)

Convertible note offering US$2.0 million Face value of promissory note facility (Dec 2025–Jan 2026)

AI data center capacity 26MW Target minimum total capacity for Finland project

Initial capacity 6MW Planned year-one capacity under AI data center plan

Annual capacity add 10MW Committed minimum additional capacity per year thereafter

Land lease term 30 years Finnish data center site in Mikkeli

Site area 101,071 square meters Designated AI data center parcel in Pellosniemi

PUE reduction 8%–15% Expected annual Power Usage Effectiveness improvement from smart cooling

Market Reality Check

Price: $0.3230 Vol: Volume 1,234,981 versus 2...

low vol

$0.3230 Last Close

Volume Volume 1,234,981 versus 20-day average of 26,011,884 shows participation remained relatively low ahead of this release. low

Technical Shares at $0.3663 are trading well below the $1.57 200-day moving average, reflecting a prior downtrend.

Peers on Argus

MASK fell 8.88% while peers were mixed: FTFT -13.19%, IFBD -3.06%, BNZI +4.14%, ...

1 Up 1 Down

MASK fell 8.88% while peers were mixed: FTFT -13.19%, IFBD -3.06%, BNZI +4.14%, IDAI +2.90%, SGN +10.70%. Momentum names JTAI +24.78% and SGN -4.70% moved in opposite directions, supporting a stock-specific move.

Historical Context

5 past events · Latest: Jan 12 (Positive)

Pattern 5 events

Date	Event	Sentiment	Move	Catalyst
Jan 12	Land lease signed	Positive	+7.9%	30-year lease securing 101,071 m² Finland AI data center site.
Jan 09	Convertible note closing	Negative	-14.3%	Subsequent closing of US$2.0M convertible note financing.
Dec 19	Convertible note initial	Negative	+0.0%	Initial closing of US$2.0M convertible promissory note offering.
Dec 15	AI MSA signed	Positive	+36.4%	Master Services Agreement for 26MW AI data center in Finland.
Oct 24	Board changes (peer)	Neutral	+3.7%	Board reshuffle at related company PINTEC with MASK board overlap.

Pattern Detected

AI-related Finland data center announcements have previously coincided with strong positive moves, while financing news has seen weaker or negative reactions.

Recent Company History

Over the past few months, 3 E Network has pivoted toward an AI data center strategy in Finland. An AI Master Services Agreement announced on Dec 15, 2025 triggered a 36.35% move, and a 30-year land lease for a 101,071 m² site on Jan 12, 2026 saw shares rise 7.89%. In contrast, a US$2.0 million convertible note offering around Dec 2025–Jan 2026 drew a -14.27% reaction and a flat response at the initial closing, highlighting sensitivity to dilution versus enthusiasm for AI infrastructure milestones.

Market Pulse Summary

The stock dropped -18.0% in the session following this news. A negative reaction despite detailed AI...

Analysis

The stock dropped -18.0% in the session following this news. A negative reaction despite detailed AI data center progress fits a pattern where the stock previously responded more strongly to financing risk than to strategy. Shares traded 91.26% below the 52-week high before this news and already sat well under the $1.57 200-day moving average, signaling a weak backdrop. In that context, investors may have focused on execution and funding risks, making pullbacks more likely even on seemingly constructive AI updates.

Key Terms

infiniBand, rdma over converged ethernet (roce), remote direct memory access (rdma), gpu, +3 more

7 terms

infiniBand technical

"3 E Network adopts InfiniBand™ Architecture or RDMA over Converged Ethernet (RoCE) technology."

Infiniband is a high-speed data transport technology used inside data centers to move large amounts of information quickly and with very little delay, often used for servers, storage and computing clusters. Investors should care because it acts like a multilane expressway for data—companies that build, use or support such fast networks can gain competitive advantages in cloud services, high-performance computing and AI workloads, which can affect costs and revenue potential.

rdma over converged ethernet (roce) technical

"adopts InfiniBand™ Architecture or RDMA over Converged Ethernet (RoCE) technology."

Remote Direct Memory Access over Converged Ethernet (RoCE) is a networking technology that lets one computer read or write data directly into another computer’s memory over an Ethernet network, skipping much of the usual software overhead. For investors, RoCE matters because it sharply reduces delays and CPU load in data centers and cloud services—think of it as a dedicated fast lane for data—so companies using it can run high‑performance applications (AI, trading, storage) more efficiently, lowering costs and improving service speed.

remote direct memory access (rdma) technical

"Through Remote Direct Memory Access (RDMA) technology, it achieves high-speed direct interconnection"

Remote Direct Memory Access (RDMA) is a technology that lets one computer read or write data directly into another computer’s memory without going through the operating system, so transfers happen much faster and use less processing power. For investors, RDMA matters because it can cut costs and improve performance in data centers, cloud services, and high-speed trading systems—similar to two coworkers passing a document directly to each other instead of routing it through a busy receptionist.

gpu technical

"high-speed direct interconnection between GPU memories, effectively eliminating bottlenecks"

A GPU (graphics processing unit) is a specialized computer chip designed to handle many calculations at once, originally for rendering images and video but now widely used for tasks like artificial intelligence, data analysis and high-performance computing. Investors watch GPU demand and prices because strong sales often signal growth for chip makers and their customers, affect profit margins and capital spending, and can forecast wider trends in gaming, AI adoption and cloud services.

internet of things (iot) technical

"3 E Network utilizes Internet of Things (IoT) sensors to continuously monitor equipment health"

The internet of things (IoT) describes a network of everyday objects—such as appliances, vehicles, and devices—that are connected to the internet and can share data automatically. This connectivity enables these objects to function more efficiently and provides valuable insights for businesses and consumers alike. For investors, IoT represents a growing area of technological innovation with the potential to transform industries and create new market opportunities.

aiops technical

"combines them with AIOps (Artificial Intelligence for IT Operations) models to predict potential faults"

AIOps (Artificial Intelligence for IT Operations) uses machine learning and data analysis to monitor, detect, and resolve problems in an organization’s technology systems automatically. It matters to investors because it can cut downtime and operating costs, speed up fixes, and make digital products more reliable—similar to an autopilot that notices and corrects issues before they disrupt service, which can protect revenue and reduce operational risk.

power usage effectiveness (pue) technical

"This scheme not only effectively lowers the Power Usage Effectiveness (PUE) value and reduces noise"

Power Usage Effectiveness (PUE) is a simple ratio that compares the total energy consumed by a data center (including cooling, lighting and other facility systems) to the energy used solely by the servers and networking equipment. For investors, a lower PUE means less energy is wasted — like a car that gets more miles per gallon — which usually translates into lower operating costs, smaller sustainability risks and a clearer picture of infrastructure efficiency.

AI-generated analysis. Not financial advice.

HONG KONG, Jan. 14, 2026 (GLOBE NEWSWIRE) -- 3 E Network Technology Group Limited (Nasdaq: MASK) (the “Company” or “3 E Network”), a business-to-business (“B2B”) information technology (“IT”) business solutions provider committed to becoming a next-generation artificial intelligence (“AI”) infrastructure solutions provider, today announced the core technical architecture of its high-performance AI data center project, following the signing of a land lease agreement with the City of Mikkeli in Finland in December 2025. 3 E Network aims to provide competitive computing services to global customers, leveraging its unique technological advantages.

The rapid advancement of artificial intelligence has revealed critical limitations in traditional data center architectures, particularly under high-intensity workloads such as large-scale model training, inference, and AI-driven applications. In response to these challenges, 3 E Network aims to redefine the standards for computing infrastructure in the AI era. Leveraging its strategic vision and technical expertise in energy investment, the Company is developing an integrated AI data center solution that combines both software and hardware capabilities.

Core Infrastructure Philosophy: Reshaping the Compute Foundation

Modular Design: Rapid Deployment

Traditional data center construction is often an 18-month-plus endeavor, involving complex design, construction, and commissioning phases. 3 E Network has adopted a modular design concept, decomposing the entire AI data center into prefabricated and interchangeable standard units. From power distribution, IT equipment to cooling and networking units, all modules are prefabricated and tested off-site before being shipped for rapid on-site assembly. This "Plug-and-Play" design not only significantly shortens the deployment timeline, but also offers unparalleled flexibility. The update or replacement of any single module can be performed without impacting the overall system's operation, enabling truly seamless, zero-downtime upgrades and expansion.

AI High-Density Computing: Advanced Performance

Facing the extreme requirements of AI workloads for computing power, the rack power density of traditional data centers (typically 3-5kW) is insufficient to meet the high energy demands of AI clusters. 3 E Network has launched a high-density computing solution that increases rack power density to 20kW or higher. This solution unleashes powerful computing capabilities within limited space, precisely matching and supporting high-intensity AI training and inference tasks.

Low-Latency, High-Availability Network: High-Speed Interconnection

Addressing the characteristics of AI scenarios—huge data transmission volumes, high bandwidth requirements, and latency sensitivity—3 E Network adopts InfiniBand™ Architecture or RDMA over Converged Ethernet (RoCE) technology. Through Remote Direct Memory Access (RDMA) technology, it achieves high-speed direct interconnection between GPU memories, effectively eliminating bottlenecks caused by CPU processing. Simultaneously, combined with a high-performance network architecture and a dual-device hot backup design for core equipment, this solution ensures both high throughput and high availability for computing clusters.

Liquid Cooling Adaptation: Green and Efficient

The leap in AI chip performance has driven an explosive growth in power consumption. The power draw of leading single-chip products, such as NVIDIA H100/H200 and the Blackwell architecture, now exceeds 700W. 3 E Network adopts a flexible "Air-Liquid Hybrid" scheme that is compatible with existing general-purpose servers while seamlessly accommodating 20kW+ high-density liquid-cooled racks. This scheme not only effectively lowers the Power Usage Effectiveness (PUE) value and reduces noise but also avoids redundant infrastructure investment caused by rapid hardware iteration.

Intelligent Operations System: Deep Optimization from Maintenance to Operations

Relying on a self-developed AI smart cooling system, the data center can collect and analyze IT load, cooling system status, and external environmental parameters in real time to dynamically optimize cooling strategies. This system is expected to reduce the annual PUE by 8% to 15%. Furthermore, by combining dynamic electricity prices and load forecasting, it intelligently schedules computing resources, transforming the data center from a mere energy consumer into an intelligent energy manager.

Smart O&M and Predictive Maintenance

3 E Network utilizes Internet of Things (IoT) sensors to continuously monitor equipment health and combines them with AIOps (Artificial Intelligence for IT Operations) models to predict potential faults in advance, significantly reducing the probability of unplanned downtime. This system enables the automation and remote centralized control of operation and maintenance (O&M) processes, which significantly lowers O&M costs while drastically boosting the productivity of the operations team.

AI Smart Security Protection

Leveraging AI algorithms to perform real-time analysis of massive logs and network traffic, the system can rapidly identify anomalous behaviors—including abnormal logins, data exfiltration, and potential internal threats—thereby building an impregnable security defense for corporate core computing assets.

About 3 E Network Technology Group Limited

3 E Network Technology Group Limited is a business-to-business (“B2B”) information technology (“IT”) business solutions provider, committed to becoming a next-generation artificial intelligence (“AI”) infrastructure solutions provider. It upholds the industry consensus of “AI and energy symbiosis” and has excellent vision in the field of energy investment. The Company’s business comprises two main portfolios: the data center operation services portfolio and the software development portfolio. For more information, please visit the Company’s website at https://3emask.com/.

Forward-Looking Statements

Certain statements in this announcement are forward-looking statements. These forward-looking statements involve known and unknown risks and uncertainties and are based on the Company's current expectations and projections about future events that the Company believes may affect its financial condition, results of operations, business strategy and financial needs. Investors can identify these forward-looking statements by words or phrases such as "approximates," "assesses," "believes," "hopes," "expects," "anticipates," "estimates," "projects," "intends," "plans," "will," "would," "should," "could," "may" or similar expressions. The Company undertakes no obligation to update or revise publicly any forward-looking statements to reflect subsequent occurring events or circumstances, or changes in its expectations, except as may be required by law. Although the Company believes that the expectations expressed in these forward-looking statements are reasonable, it cannot assure you that such expectations will turn out to be correct, and the Company cautions investors that actual results may differ materially from the anticipated results and encourages investors to review other factors that may affect its future results in the Company's registration statement and other filings with the U.S. Securities and Exchange Commission.

For more information, please contact:

3 E Network Technology Group Limited
Investor Relations Department
Email: ird@3emask.com
Website: https://3emask.com/

FAQ

What did 3 E Network (MASK) announce on January 14, 2026 about its AI data center?

The company unveiled the core architecture for a modular, high-density AI data center and said it signed a land lease in Mikkeli, Finland in Dec 2025.

How dense are the racks in 3 E Network's MASK AI data center design?

The design targets 20kW or higher rack power density to support large-scale AI training and inference.

What energy efficiency improvement does 3 E Network (MASK) expect from its smart cooling?

The company expects a 8%–15% annual PUE reduction via an AI-driven smart cooling and scheduling system.

Which networking technologies will MASK use to reduce AI latency and bottlenecks?

3 E Network plans to use InfiniBand or RoCE (RDMA) to enable high-speed GPU-to-GPU interconnects and lower latency.

Will 3 E Network's MASK data center support liquid cooling for modern AI chips?

Yes; the architecture uses an air-liquid hybrid approach compatible with 20kW+ liquid-cooled racks to handle high chip power.

How does 3 E Network (MASK) plan to reduce downtime and O&M costs?

The company uses IoT sensors and AIOps for predictive maintenance and centralized remote O&M to lower unplanned downtime and costs.