3 E Network Advances Proprietary AI SaaS Platform for Companion Robots

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 ten