LAS VEGAS — At CES 2026, the world’s leading consumer and enterprise technology event, MICROIP Inc. (Emerging Stock Board: 7796), a Taiwan-based provider of ASIC design services and AI software solutions, is showcasing its latest advancements at the AI Applications Pavilion. The company is presenting its CAPS (Cross-Platform AI Powered Solutions) architecture and highlighting AIVO (AI Vision Operation), a flagship Edge AI platform that has already entered commercial deployment.

Through a software-defined approach, MICROIP demonstrates how AI applications can be deployed across global environments with lower barriers to entry and higher operational efficiency—bridging the gap between proof-of-concept and real-world deployment.

From Technology Demonstration to Operational AI

Dr. James Yang, Chairman of MICROIP, stated:

“CES is not just a venue for showcasing technology—it is where AI must prove its real-world value. AIVO was not designed to maximize model benchmarks or raw hardware performance, but to address real deployment constraints in transportation security, smart agriculture, and autonomous systems, including heterogeneous network conditions, limited edge compute resources, and long-term operational costs.

By starting from these real-world constraints, MICROIP has built AIVO as an Edge AI platform that can be deployed, operated, and maintained over time—allowing AI to become part of daily operations rather than remaining at the proof-of-concept stage.”

CES 2026 Focus: Turning Edge AI into Operational Capability

CAPS is MICROIP’s cross-platform AI software design framework, developed to help customers define AI systems that are deployable and maintainable in production environments. At CES 2026, MICROIP presents AIVO as a reference implementation of CAPS, demonstrating how Edge AI evolves from pilot projects into scalable, operational systems.

Positioned as the deployment-focused pillar within the CAPS architecture, AIVO addresses two of the most persistent challenges in Edge AI: bandwidth constraints and multi-task processing at the edge.

Distributed Master–Client Architecture for Large-Scale Edge Deployment

To support geographically distributed and large-scale deployments, AIVO adopts a master–client distributed architecture. Real-time inference is performed locally on edge devices, while system management and decision logic are centralized at the host level.

Instead of streaming raw video data, edge nodes transmit only structured inference results and metadata. This design significantly reduces bandwidth requirements and allows the system to maintain centralized oversight and real-time responsiveness—even in 4G/5G or unstable network environments.

Real-Time Heterogeneous Multi-Tasking at the Edge

AIVO integrates a dynamic resource scheduling mechanism that enables multiple AI models to run concurrently on a single hardware platform. In security scenarios, object detection, behavior analysis, and environmental sensing models can operate in parallel, with compute resources allocated dynamically based on task priority.

This ensures that mission-critical events are processed and responded to in real time, even under constrained edge compute conditions.

Proven Edge AI Applications Across Transportation, Agriculture, and Autonomous Systems

Leveraging its system architecture, AIVO has completed multiple international field validations and is now focused on high-reliability application domains worldwide:

Transportation Security:
AIVO is being rolled out across metro systems, railways, buses, commercial aviation, and airport environments. Edge-based AI enables real-time detection of anomalous behavior, with alerts integrated into control centers or government security systems—enhancing response capability without increasing manpower requirements.

Smart Agriculture:
Addressing labor shortages and an aging workforce in U.S. agriculture, AIVO uses computer vision to monitor livestock health and environmental conditions. Expert knowledge from experienced farmers is encoded into AI models, while optimized system design ensures stable operation under low-power and limited-network farm environments.

AI Drones and Robotics:
For infrastructure inspection and disaster response, AIVO strengthens on-device autonomy. Even in GPS-denied or connectivity-limited conditions, drones and robots can perform real-time object tracking and dynamic obstacle avoidance, expanding the use of autonomous systems in high-risk scenarios.

CAPS Ecosystem: Software-Driven Hardware Through Global Partnerships

Dr. Yang emphasized that CAPS represents MICROIP’s holistic vision for AI software design services:

“Through vertical integration of AIVO as the deployment platform, XEdgAI as the system development platform, and CATS as our custom ASIC service, we establish a core advantage where software defines hardware specifications and real-world applications validate design direction.”

To accelerate global adoption of this model, MICROIP announced at CES 2026 strategic partnerships with Axelera AI (Europe), Axiomtek, Lex System, and U.S.-based Physical AI and robotics integration startup Universal AI Services, forming an international Edge AI alliance.

Through CAPS’ cross-platform compatibility, MICROIP has integrated mainstream AI chip platforms with industrial-grade hardware to deliver end-to-end, software-defined hardware Edge AI solutions. This strengthens MICROIP’s technical leadership within the Edge AI ecosystem and enables customers worldwide to deploy high-performance, low-power AI systems across transportation, agriculture, and robotics applications.

CES 2026 Exhibition Information – Next-Generation Edge AI Solutions

• Dates: January 6–9, 2026

• Location: Las Vegas, USA

• Hall: North Hall

• Booth: #9277