HONG KONG, July 22, 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 that it is developing an enterprise-grade AI software-as-a-service ("SaaS") platform designed for smart companion and eldercare robots. Following its recent announcement that it had finalized the architecture of its custom edge AI system-on-chip ("SoC"), this initiative is intended to strengthen 3 E Network’s position as a full-stack embodied AI infrastructure provider built around "Edge-Cloud Synergy" and expand the Company’s presence in AI cloud services with potential recurring revenue streams.
As embodied AI hardware continues to mature, the Company believes that edge hardware establishes the foundation for a robot’s physical interaction, while the cloud-based software and operational capabilities help determine its cognitive capabilities and commercial scalability. The SaaS platform under development by 3 E Network is intended to provide a robust "cloud brain" and comprehensive system-level support for a range of intelligent companion devices.
Three Core Business Modules: AI-Enabled Cognition and Lifecycle Management
This enterprise-grade SaaS platform aims to provide comprehensive operational support for healthcare institutions, eldercare facilities, and service robot manufacturers. Its three core business modules include:
- Generative AI Companion Agent and Multimodal Affective Engine: By integrating multimodal interactive frameworks developed by leading AI providers, this module moves beyond traditional scripted interactions, enabling companion robots to function as proactive AI agents. Through long-term multimodal affective computing and contextual modeling, the system analyzes emotional cues in seniors’ real-time interactions. It generates context-aware responses designed to demonstrate empathy, improving the naturalness of human-robot interactions and the quality of companionship.
- Predictive AI Monitoring and Low-Latency Risk Escalation: Benchmarking against the strict, high-reliability data standards established in professional healthcare, the platform is designed to provide a low-latency, high-reliability data pipeline from edge terminals to backend systems. The system not only detects abnormal fluctuations in vital signs in real time but also utilizes AI time-series models to identify potential safety risks associated with user behavior, such as falls. When a preset threshold is reached, it initiates "Intelligent Event Routing," pushing structured alerts to designated licensed caregivers, supporting a seamless "monitor-alert-intervene" closed loop.
- Digital Twin Fleet Management and Robot Ops Hub: Targeting the complex operational requirements of large fleets of intelligent devices, this hub provides enterprise clients with an integrated digital-twin management interface. Clients can not only monitor the operational status of massive robotic fleets in real time but also conduct shadow testing evaluations and OTA batch deployments for cloud AI strategies with reduced risk, supporting scalable and efficient maintenance of deployed devices.
Four Key Underlying Technologies: Enabling an Advanced Cloud Infrastructure Platform
To support complex business concurrency and enterprise-grade data security, 3 E Network’s software team is developing the following core technological foundation for the SaaS platform:
- Cloud-Native and Multi-Tenant Architecture: The platform uses a highly available microservices architecture with strict tenant-isolation controls. This ensures elastic scalability when handling concurrent requests across different markets, while maintaining physical and logical data isolation between institutional clients.
- Edge-Cloud Collaborative LLM Routing Engine: Working in tandem with the Company’s proprietary edge computing hardware, the platform features a dynamic model routing engine. It intelligently evaluates task complexity: basic interactions can be processed in real time by quantized models at the edge, while complex long-context reasoning and professional caregiving Q&A are dynamically routed to cloud-based models for more advanced processing, continuously optimizing compute cost, latency, and output quality.
- Retrieval-Augmented Generation ("RAG") Knowledge Enhancement and Vector Memory Sandbox: The system deeply integrates RAG technology, supporting the flexible integration of professional nursing knowledge bases to reduce the risk of inaccurate or fabricated AI outputs. In addition, the system establishes an isolated cloud-based "Vector Sandbox" for each terminal, designed to securely store users’ preferences and historical interaction data to support a more personalized companion experience.
- Medical-Grade Encryption and Lifecycle Compliance: To support compliance with applicable privacy requirements, including HIPAA where applicable, the platform establishes bi-directional encrypted transmission protocols with forward secrecy. Core interaction data is designed to undergo edge-side de-identification procedures before being uploaded, supporting compliance throughout the cloud data-processing lifecycle.
Dual-Engine Business Model: Upgrading from "Hardware Delivery" to "Recurring Cloud Subscriptions"
Dr. Tingjun Yang, Chief Executive Officer of 3 E Network, commented: "While our previously announced edge AI SoC provides a powerful ‘edge-based perception foundation,’ the AI SaaS platform complements it with a cloud platform capable of supporting more advanced cognitive functions. The synergy of these two elements is intended to create a comprehensive technology platform built around Edge-Cloud Synergy."
"From a long-term commercial perspective, the architecture of this SaaS platform holds strategic significance for the Company. It enables the Company to empower a broader range of global service robot hardware manufacturers. More importantly, it supports the evolution of 3 E Network’s business model from traditional ‘one-time hardware delivery’ to a dual-engine model combining a ‘hardware compute foundation with recurring cloud-based SaaS subscriptions.’ We believe this model can enhance the resilience of our revenue base and create long-term growth opportunities for the Company within the global silver economy."
Currently, the core microservices architecture and edge-cloud collaborative data pipelines of this enterprise-grade AI SaaS platform have been finalized. The Company’s R&D team is actively advancing the scenario-specific fine-tuning of multimodal affective large models and integrating the platform with relevant business workflows. Concurrently, to address data-security and business-continuity requirements, the platform is undergoing enterprise-grade testing of its multi-tenant isolation controls and end-to-end system availability. These engineering and testing efforts are intended to strengthen the platform’s enterprise-grade architecture, supporting the Company’s future global commercial rollout and potential SaaS revenue generation.
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 a strong 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 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 the Company’s 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/
