HONG KONG, Feb. 05, 2026 (GLOBE NEWSWIRE) -- 3 E Network Technology Group Limited (Nasdaq: MASK, "3 E" or the "Company"), a business-to-business ("B2B") information technology ("IT") business solutions provider advancing toward next-generation artificial intelligence ("AI") infrastructure solutions, today announced the implementation of its "AI Smart Energy Plan" in connection with the AI Data Center in Mikkeli, Finland. Intended to serve as a top-level planning framework for the construction phase, this blueprint leverages the Company's proprietary innovations in the Internet of Things (IoT) and data intelligence. Through the design of five core technical modules, the plan is designed to support full-chain control over operational energy usage. The initiative aims to optimize Power Usage Effectiveness (PUE) via technological intervention, supporting a transition from traditional "passive consumption" toward "active management."

Amidst surging computing demand and fluctuating conditions in European energy markets, energy efficiency has become an increasingly important factor in the economics of data center operations. Dr. Tingjun Yang, CEO of 3 E, said: "For high-density AI computing centers, electricity is not merely a cost but a strategic asset. The Company is designing the Mikkeli project with the objective of improving energy efficiency through algorithm-driven management approaches. By aligning computing workloads with real-time market signals, this framework is intended to support more efficient energy utilization over time, subject to market and operational conditions."

The newly released Smart Energy Plan encompasses the following proposed key technical pillars:

  • Construction of Omni-Domain High-Frequency Sensing System: Utilizing a dense IoT sensor network, the system is designed to generate a high-frequency, full-state digital mapping of the physical environment. By aggregating multi-dimensional data—spanning IT load characteristics, chiller operating status, and outdoor meteorological conditions—the system is designed to generate high-precision decision inputs for AI algorithms, with the objective of reducing blind spots and enhancing operational visibility.
  • Implementation of AI-Adaptive Closed-Loop Tuning: Building upon and extending beyond traditional static configurations, the system is designed to employ machine learning models to execute closed-loop control over cooling strategies. It is intended to dynamically align fan speeds and refrigerant flow rates with real-time thermal loads, supporting precise "cooling-on-demand." This mechanism is expected to help reduce energy waste, ensuring the facility continuously operates within its optimal designed PUE range.
  • Development of High-Precision Price Prediction Models: Tailored to the characteristics of the regional power market, this module is designed to utilize time-series forecasting technology to decode grid supply and demand trends. It is intended to generate forward-looking price trend signals that may serve as an important input for economic workload scheduling.
  • Establishment of Economic Workload Dispatch Mechanism: Creating a synergistic "Compute-Energy" response protocol. Guided by predictive pricing signals, the system is designed to support automate task orchestration: while seeking to maintain the Service Level Agreement (SLA) of critical tasks, it automatically migrates high-intensity large-scale training workloads to off-peak price windows. This strategy is intended to support optimization of the Operational Expenditure (OPEX) structure.
  • "Passive Consumption" to "Active Management": Reframing the interaction logic between the infrastructure and the power grid. Through integrated Demand Response modules, the facility is designed to support bidirectional regulatory capabilities. The system may adjust power consumption to assist grid balancing based on utility instructions to support grid balancing efforts, with the potential to integrate more closely into the local green energy ecosystem and explore ancillary service opportunities.

This "AI Smart Energy Plan" represents a strategic framework developed by the Company that draws on its technological capabilities to support the operational performance of the Mikkeli project. In an era where energy efficiency plays an increasingly important role in AI computing margins, this algorithm-driven management model is intended to enhance the Company's resilience against energy price fluctuations over time, supporting more sustainable cost management. Furthermore, by embedding "green sustainability" into its core business logic, the plan is designed to align with strict Nordic environmental standards and may serve as a standardized reference framework for future global expansion, supporting a competitive position within the industry.

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: [email protected]

Website: https://3emask.com/