en.Wedoany.com Reported - On June 2, Lanner Electronics, a network equipment and edge computing platform company from Taiwan, China, announced that it will showcase an end-to-end AI-on-RAN solution during Computex 2026 in collaboration with Qualcomm Technologies, Askey Computer, Saviah Technologies, and Ecrio. This solution integrates private 5G networks, real-time communications, and edge AI inference into a single architecture, providing a low-latency intelligent network foundation for industrial, enterprise private network, and critical communication scenarios.
The core of this demonstration is advancing private 5G networks from mere connectivity to an enterprise infrastructure that integrates "connectivity + computing + communication coordination." Traditional enterprise networks primarily handle data transmission tasks, while AI inference, video analysis, production alerts, and personnel coordination often run on independent servers or cloud platforms, creating scheduling gaps between the network and computing. The AI-on-RAN architecture showcased by Lanner uses the ECA-5555 edge AI platform as its core, serving as both an edge computing system and a core server. Combined with Qualcomm's Dragonwing solution and the AI 100 Ultra inference accelerator, it processes latency-sensitive AI workloads at the network edge. For scenarios such as smart manufacturing, logistics, field operations, and industrial safety, visual inspection, anomaly detection, voice coordination, and equipment status feedback need to be completed locally and quickly. The integration of private 5G networks with edge inference reduces data backhaul pressure and improves on-site response speed.
The wireless connectivity component of the solution consists of the Askey SCU5000 Small Cell and the Saviah 5G Core, providing secure, low-latency private 5G coverage.
Real-time communication capabilities are provided by Ecrio, with IMS/SIP-based VoIP services supporting push-to-talk and real-time voice collaboration. This connects AI inference results with personnel handling processes in industrial sites, logistics parks, and field operations. In other words, when cameras, industrial IoT sensors, or on-site terminals detect anomalies, the system can not only complete inference at the edge but also trigger voice, video, or message collaboration, allowing personnel to directly participate in the handling process. The demonstration also includes visual language model capabilities being advanced by Edge Impulse, aiming to form a multi-layer AI processing chain between terminal devices and the network edge: lightweight visual inspection can be completed closer to the device, while complex inference is handled by a unified edge server, achieving a balance between bandwidth, latency, and computing power.
From the perspective of the communication network industry, AI-on-RAN is transforming private 5G from an "enterprise wireless private network" into an operating platform for industrial intelligent applications. In the past, enterprise deployment of 5G private networks focused primarily on coverage, reliability, isolation, and mobile terminal access. As AI applications enter production sites, network nodes themselves are beginning to take on more local computing and intelligent scheduling tasks. The demonstration ecosystem formed by Lanner, Qualcomm, Askey, Saviah, and Ecrio covers multiple aspects including edge servers, small cells, 5G core networks, real-time communication software, AI inference acceleration, and visual model development, indicating that enterprise-grade 5G networks have entered the stage of cross-vendor system integration. Future commercialization variables will focus on equipment costs, deployment complexity, industry application adaptation, operational capabilities, and whether enterprises can directly link private network construction with actual productivity improvements.
For manufacturing and large enterprise users, the appeal of such solutions lies in the fact that on-site data does not need to rely entirely on public networks or remote cloud platforms. Sensitive video, production status, and critical communications can be processed in a closed loop locally. As demand for industrial automation, machine vision, unmanned inspection, smart warehousing, and emergency communications increases, private 5G networks will take on more complex business roles. Lanner's demonstration of the AI-on-RAN solution in collaboration with ecosystem partners provides a blueprint for enterprises to deploy communication networks, edge computing power, and real-time collaboration in a unified manner, shifting the focus of news within the communication network subcategory from operator core networks to enterprise on-site infrastructure.
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