POWERED BY NVIDIA JETSON THOR T4000, THE EDGECOMP MS-NAT4000 BRINGS HIGH-DENSITY AI PERFORMANCE, ON-DEVICE GEN-AI, AND REAL-TIME SENSOR PROCESSING TO INDUSTRIAL EDGE DEPLOYMENTS
July 7th, 2026, TAIPEI, TAIWAN – BIOSTAR, a leading manufacturer of edge computing solutions, industrial motherboards, graphics cards, and storage devices, today introduces the EdgeComp MS-NAT4000, a compact edge AI computing system designed to support the NVIDIA® Jetson Thor T4000 module for high-performance AI computing, real-time sensor processing, and intelligent automation at the edge.
Built for system integrators, AI software developers, smart manufacturing solution providers, and advanced autonomous machine builders, the EdgeComp MS-NAT4000 is engineered to bring greater AI computing density closer to where data is generated. With support for on-device generative AI, visual intelligence, low-latency sensor fusion, and simultaneous AI workloads, the platform provides a powerful foundation for industries deploying AI-driven systems in real-world environments.
As AI applications move from cloud-dependent processing to real-time edge deployment, industries require compact computing platforms that can analyze large volumes of data locally while maintaining low latency, high efficiency, and flexible system integration. The EdgeComp MS-NAT4000 is designed to meet these requirements, enabling applications such as smart manufacturing inspection, autonomous mobile robots, intelligent surveillance, smart city infrastructure, unmanned delivery systems, and industrial automation.
Powered by NVIDIA Blackwell architecture through the Jetson Thor T4000 module, the EdgeComp MS-NAT4000 delivers up to 1200 TFLOPS of FP4 AI performance, achieving a 4.3× speed boost and 3.5× energy efficiency improvement compared to AGX Orin. Equipped with 64GB 256-bit LPDDR5X memory and a 12-core Arm CPU, the system is built to support demanding AI workloads, including large language models, vision-language models, AI agents, real-time inference, and advanced computer vision applications.
This high-performance architecture enables powerful AI models to run locally at the edge, reducing reliance on cloud infrastructure while improving responsiveness, data privacy, and deployment flexibility. For industrial and autonomous applications where fast decision-making is critical, on-device AI processing allows systems to analyze data, respond to changing conditions, and execute intelligent actions in real time.
To support high-bandwidth sensor and vision workloads, the EdgeComp MS-NAT4000 features 2 x 5 GbE LAN ports and 1 x QSFP28 connector, supporting up to 3 x 25 GbE connections. Paired with NVIDIA Holoscan Sensor Bridge technology, the platform enables real-time ingestion and processing of high-bandwidth camera and sensor data, making it well-suited for multi-camera inspection systems, robotics perception, intelligent monitoring, and other sensor-rich AI deployments.
Designed for flexible edge integration, the EdgeComp MS-NAT4000 provides a comprehensive set of expansion, storage, display, and industrial I/O options in a compact 192 x 154 x 80 mm system. It supports 1 x M.2 Key M slot for 2260/2280 PCIe 5.0 x4 NVMe storage, 2 x SATA III ports with optional SSD hot-swap tray support, 1 x M.2 Key B 3042/3052 slot with USB 3.2 for LTE/5G module expansion, and 1 x M.2 Key E 2230 slot with PCIe 5.0 x1 and USB 2.0 for Wi-Fi and Bluetooth modules.
For display output, the system provides 1 x HDMI® supporting up to 3840 x 2160 at 60Hz and 1 x DP 1.4a, enabling high-resolution visual output for AI monitoring, machine vision, industrial control, and digital operation interfaces. Its external I/O includes 4 x USB 3.2 Gen2 Type-A ports, 1 x USB 3.2 Type-C port for OS flashing, 2 x RS232/422/485 COM ports, line-in and line-out audio, power, recovery, and reset buttons, TPM 2.0 support, and a 12–36V DC terminal block for industrial power input.
Built for practical deployment, the EdgeComp MS-NAT4000 is powered by a 240W adapter and supports JetPack 7.1 with Linux Kernel 6.8 and Ubuntu 24.04. With a net weight of 1.79 kg, support for 0°C to 50°C operating temperatures, 5% to 90% humidity tolerance, 5 Grms vibration resistance, and 30G shock resistance, the system is designed to operate reliably in demanding edge environments.
Across smart manufacturing, the EdgeComp MS-NAT4000 can support automated optical inspection, predictive maintenance, production line monitoring, and AI-assisted human-machine collaboration. In intelligent surveillance and smart city applications, it enables real-time video analytics, anomaly detection, traffic monitoring, and infrastructure intelligence. For autonomous mobile robots, unmanned delivery vehicles, and heavy-duty automated machinery, the platform provides the AI computing capability required for perception, navigation, sensor fusion, and real-time decision-making.
The EdgeComp MS-NAT4000 further strengthens BIOSTAR's EdgeComp portfolio, reflecting the company's continued commitment to delivering reliable, compact, and integration-ready computing platforms for next-generation edge AI deployments. By combining support for NVIDIA Jetson Thor T4000, high-speed networking, flexible expansion, industrial-grade connectivity, and robust system design, BIOSTAR provides system integrators and AI solution developers with a powerful platform for bringing advanced AI capabilities into practical edge environments.
Product Page: EdgeComp MS-NAT4000 Product Page
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