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      Innodisk Unveils Scalable, Integrated Edge AI Portfolio at Embedded World 2026


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      Innodisk Corporation

      10 мар, 2026, 12:32 GMT

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      NUREMBERG, Germany, March 10, 2026 /PRNewswire/ -- Innodisk, a leading global AI solution provider, presents a comprehensive portfolio designed to accelerate real-world edge AI deployment at Embedded World 2026. With a strong focus on enterprise and industry AI, Innodisk bridges advanced computing performance with practical system integration to enable scalable, secure, and high-efficiency edge AI implementation.

      Bridging Enterprise AI and Edge Inference

      Continue Reading
      Innodisk unveils scalable, integrated Edge AI portfolio at Embedded World 2026
      Innodisk unveils scalable, integrated Edge AI portfolio at Embedded World 2026

      At the core of this year's showcase are Innodisk's on-prem enterprise AI solutions. AccelBrain provides secure, air-gapped AI inference, keeping data private and enabling fast, local AI processing on the Innodisk APEX-X200 edge AI system powered by the latest NVIDIA® Blackwell GeForce RTX™ 5080 GPU. AccelTune allows enterprises to fine-tune models without coding, using the Innodisk APEX-S100 edge AI system with Intel® Xeon® 6700-series processors and support for dual NVIDIA® H200, RTX PROᵀᴹ 6000 Blackwell Server Edition, or L40S GPUs, making model training and optimization simpler and more scalable. These solutions help enterprises keep sensitive data secure and process AI in real time on-site.

      Multi-Platform Solutions: Qualcomm and Intel Collaborations

      Leveraging its expertise in system integration, Innodisk collaborates with leading industry partners to deliver multi-platform solutions for diverse edge AI needs. In partnership with Qualcomm Technologies, Inc., Innodisk highlights its AI on ARM computing series, including the COM-HPC Mini Module and Starter Kit powered by Qualcomm Dragonwing™ processors. Delivering up to 100 TOPS (Dense) of scalable AI performance, these systems are built on a robust Dragonwing architecture designed to support increasingly complex edge AI workloads while maintaining energy efficiency and flexible system integration for industrial environments.

      Powered by the Dragonwing platform, live demonstrations showcase Vision Language Model (VLM) applications for real-time scene understanding, including smoke and fire detection, PPE compliance, and worker fall detection, alongside AI-powered NVR systems that enable natural-language video search across surveillance streams.

      Expanding its collaboration with Intel, Innodisk presents edge AI solutions powered by the latest Intel® Core™ Ultra Series 3 processors, delivering up to 180 TOPS of AI computing performance for industrial applications. In addition, Innodisk showcases another live demonstration built on Intel® Core™ Ultra 200S Series processors. It features Ultra-Fast Stream OCR, showcasing zero-latency text capture and intelligent structural extraction optimized for high-speed, edge-native deployment in complex industrial environments.

      Ruggedized Camera Solutions for Edge AI

      Beyond computing platforms, Innodisk also demonstrates its ruggedized camera solutions designed for edge AI applications in mobility, robotics, and automation. Its intelligent mobility system integrates up to eight GMSL2 camera modules to enable real-time surround-view stitching, object detection, blind-spot detection, and driver-monitoring systems for heavy machinery and vehicles.

      Future-Ready AI Infrastructure

      Complementing its AI platforms, Innodisk introduces advanced AI infrastructure, including DDR5 12800 MRDIMM, CXL Add-in-Card, and LPCAMM2 solutions. High-speed LAN modules and PCIe Gen 5 data center SSDs further ensure the performance, scalability, and data bandwidth needed for demanding AI workloads.

      Visit Innodisk at Hall 1, Stand 1-370 to experience the future of edge AI. For more information, please visit www.innodisk.com.

      Photo - https://mma.prnewswire.com/media/2930310/Press_Photo__Innodisk_at_Embedded_World_2026.jpg 

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