{"title":"Sima.Ai | Official Page","description":null,"products":[{"product_id":"sima-ai-mlsoc-devkit","title":"SiMa.ai MLSoC DevKit 2.0","description":"\u003ch1 style=\"text-align: center;\" class=\"text-center lg:text-left text-white mb-4 lg:mb-8\"\u003e\u003cspan class=\"font-denim-medium text-[36px] md:leading-[40px] md:text-[64px] md:leading-[70px]\"\u003eElevate Your ML Journey\u003c\/span\u003e\u003c\/h1\u003e\n\u003cp\u003e\u003cmeta charset=\"UTF-8\"\u003e\u003cspan\u003eSiMa.ai’s MLSoC Development Kit contains everything you need to evaluate, prototype and demonstrate your computer vision ML applications on the developer board using the contained MLSoC purpose-built silicon from SiMa.ai. The Development Kit combines a compact Developer Board based upon SiMa's HHHL PCIe production board that has been modified to expose interfaces utilized by developers and accommodates operation stand-alone on a lab bench environment as well as able to embed in a PCIe platform. This on-bench or in PC configuration options offer flexibility to support different developer profiles.\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003ch2\u003e\u003cspan\u003e \u003c\/span\u003e\u003c\/h2\u003e\n\u003ch2\u003e\u003cspan\u003eOut of the Box\u003c\/span\u003e\u003c\/h2\u003e\n\u003cp\u003e\u003cspan\u003eDevelopers want to get the tools and hardware up and running quickly so they can evaluate and learn the new SiMa.ai edge ML platform. The Developer Kit provides an Out-of-Box set of all components that you need and a guide to make this a breeze and let developers focus on their evaluation.\u003c\/span\u003e\u003c\/p\u003e\n\u003cdiv style=\"text-align: center;\"\u003e\u003cimg src=\"https:\/\/sima.ai\/wp-content\/uploads\/2024\/12\/image-1-1.webp\" style=\"margin-bottom: 16px; float: none;\"\u003e\u003c\/div\u003e\n\u003ch2 style=\"text-align: left;\"\u003e \u003c\/h2\u003e\n\u003ch2 style=\"text-align: left;\"\u003eEvaluate\u003c\/h2\u003e\n\u003cp style=\"text-align: left;\"\u003e\u003cmeta charset=\"UTF-8\"\u003e\u003cspan\u003eThe first step an ML developer will want to do is establish the ML model performance and accuracy on a target platform and assess the capabilities, time and effort in compiling models of interest. Palette™ provides quantization and compilation of a developer’s model using Palette’s compiler. Utilize Palette’s silicon software image build and deploy tools to program the developer board. The developer kit provides the ability to execute these builds and provide KPIs such as; frames per second (fps), latency, accuracy, % loading of compute resources and memory footprint. Palette, running in a Docker on a desktop, supports ARM cross compilation with libraries to generate code for the SoC, a platform build, test and deploy tool suite to create complete ML applications.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch2 style=\"text-align: left;\"\u003e\u003cspan\u003e \u003c\/span\u003e\u003c\/h2\u003e\n\u003ch2 style=\"text-align: left;\"\u003e\u003cspan\u003ePrototype\u003c\/span\u003e\u003c\/h2\u003e\n\u003cp style=\"text-align: left;\"\u003e\u003cspan\u003eThe next step an ML developer will want to do is integrate this model into a potential application or use case, including ML model pre and post processing functions. To accelerate the prototyping phase, Palette adds the ability to quickly code, build and evaluate a pipeline using your own ML models. Developers can Python scripting using SiMa APIs for the functional pipeline, avoiding the complex embedded optimization often needed for on-device execution. These APIs bind your Python code to the device execution environment and will execute on device as a complete functioning pipeline. Pushbutton build and deploy loads this image into the Developer board for execution. This proof-of-concept application can validate the functionality of the pipeline as well as provide an early demonstration vehicle.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch2 style=\"text-align: left;\"\u003e\u003cspan\u003eDemonstrate\u003c\/span\u003e\u003c\/h2\u003e\n\u003cp\u003e\u003cspan\u003eQuickly bring a real-time data stream to the platform, execute a pipeline on this data stream and display the performance results in real-time running on the MLSoC silicon for use case demonstrations. GStreamer example pipelines included in the Palette software release can be run out of the box to demonstrate real-time streaming performance. Customer pipelines can leverage these pipeline designs that take advantage of GStreamer to get higher utilization of compute resources and higher fps. The developer board processes the pipelines and displays the metadata overlaid on the host PC. Add additional cameras to provide multi-camera processing capabilities.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch2\u003e \u003c\/h2\u003e\n\u003ch2\u003eMLSoC Developer Board:\u003c\/h2\u003e\n\u003cp\u003eThe MLSoC Developer Board is based upon our PCIe half-height, half-length production board but is modified to operate on a lab bench environment with access to is a versatile board that uses the SiMa.ai Machine Learning System on Chip (MLSoC) device.\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eOn Bench:\u003c\/strong\u003e PCIe edge connector covered in protective coating and a plate with four footings under the board, a micro-USB connector provides power for operation on a lab bench.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIn PCs:\u003c\/strong\u003e The PCIe form factor (68.9mm x 160mm) using a standard 98-pin PCB edge connector to slot into any standard host PC or motherboard. A bracket is included to assist in securing to a PC.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eLow Power Board: \u003c\/strong\u003eTypical workloads 10-15W. Supports PCIe Gen 4.0 up to x8 lanes, LPDDR4 x4, I2C x2, eMMC, uSD card, QSPI-8 x1, 1G Ethernet x2 ports via RJ45, UART x2, and GPIO interfaces.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMachine Learning Accelerator (MLA):\u003c\/strong\u003e providing up to 50 Tera Ops Per Second (50 TOPS) for neural network computation.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eApplication Processing Unit (APU)\u003c\/strong\u003e: a cluster of four ARM Cortext-A65 dual threaded processors operating up to 1.15 GHz to deliver up to 15K Dhry stone MIPs, eliminates the need for an external CPU or PC host.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eVideo Encoder\/Decoder:\u003c\/strong\u003e supports the H.264\/H.265 compression standards with support for baseline\/main\/high profiles, 4:2:0 sub sampling with 8-bit precision. The encoder supports rates up to 4Kp30, while the decoder supports up to 4Kp60\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eComputer Vision Unit (CVU):\u003c\/strong\u003e\n\u003cul\u003e\n\u003cli\u003econsists of a four core Synopsys ARC EV74 video processor supporting up to 600 16-bit GOPS\u003c\/li\u003e\n\u003cli\u003eIncorporated for optimized execution of computer vision algorithms used in ML pre and post processing and other pipeline processing functions\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003e \u003c\/h2\u003e\n\u003ch2\u003eContained in Development Kit 2:\u003c\/h2\u003e\n\u003ctable style=\"width: 100%\" width=\"100%\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 0px; text-align: center; vertical-align: top; width: 19.4495%;\"\u003e \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/aGroup-272.svg?v=1737478186\" alt=\"\"\u003e\u003cbr\u003eDeveloper Board (HHHL)\u003c\/td\u003e\n\u003ctd style=\"border: 0px; text-align: center; vertical-align: top; width: 31.7431%;\"\u003e\n\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/aGroup-273.svg?v=1737478186\" alt=\"\"\u003e\u003cbr\u003eType C Power adaptor \u0026amp; Type C to micro USB – cable\u003c\/td\u003e\n\u003ctd style=\"border: 0px; text-align: center; vertical-align: top; width: 13.578%;\"\u003e\n\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/Group-274.svg?v=1737478186\" alt=\"\"\u003e\u003cbr\u003eEthernet Cable\u003c\/td\u003e\n\u003ctd style=\"border: 0px; text-align: center; vertical-align: top; width: 15.7798%;\"\u003e\n\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/Group-275.svg?v=1737478186\" alt=\"\"\u003e\u003cbr\u003eUART Cable to USB\u003c\/td\u003e\n\u003ctd style=\"border: 0px; text-align: center; vertical-align: top; width: 17.9817%;\"\u003e\n\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/Group-276.svg?v=1737478186\" alt=\"\"\u003e\u003cbr\u003ePCIe Mounting Bracket\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003ch2\u003eDevelopment Kit 2 Camera Bundle:\u003c\/h2\u003e\n\u003cp\u003e\u003cspan style=\"color: rgb(128, 128, 128);\"\u003e\u003cstrong\u003eDevelopment Kit 2 with Camera bundle to demonstrate GStreamer ML pipelines in real-time\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eRouteCAM_CU20 – Sony® IMX462 Full HD GigE Camera\u003c\/li\u003e\n\u003cli\u003ePower-over-Ethernet camera with IEEE 802.3af compliance\u003c\/li\u003e\n\u003cli\u003eComes with PoE power adapter and cable\u003c\/li\u003e\n\u003cli\u003eHouses Sony® Starvis IMX462 CMOS image sensor\u003c\/li\u003e\n\u003cli\u003eUltra-low light sensitivity \u0026amp; Superior near-infrared performance\u003c\/li\u003e\n\u003cli\u003eHigh Dynamic Range (HDR)\u003c\/li\u003e\n\u003cli\u003eOn-board high-performance ISP\u003c\/li\u003e\n\u003cli\u003eSupports 10Base-T, 100Base-TX and 1000base-T-modes\u003c\/li\u003e\n\u003cli\u003eDeveloper Kit Bundled with 1GB Ethernet Camera\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"SiMa.ai","offers":[{"title":"DevKit Only","offer_id":49828686627133,"sku":"SBC1114","price":209999.99,"currency_code":"INR","in_stock":true},{"title":"DevKit Camera Bundle","offer_id":49828686659901,"sku":"SBC1114C","price":244999.99,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/Screenshot2024-01-19at12.08.51PM.png?v=1737476891"},{"product_id":"sima-ai-modalix-devkit-3-0","title":"SiMa.ai Modalix DevKit 3.0","description":"\u003ch2 style=\"text-align: center;\"\u003eModalix DevKit 3.0\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003eThe SiMa.ai MLSoC Modalix Development Kit (DevKit) is a complete hardware and software platform for evaluating and prototyping intelligent Physical AI applications using the latest MLSoC Modalix System-on-Module (SoM).\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eDesigned for rapid deployment, this kit enables seamless development, benchmarking, and proof-of-concept creation with SiMa.ai’s Palette software, offering best-in-class performance-per-watt in a compact form factor. Ideal for industrial, robotics, and vision-based and LLM-based applications, this kit supports real-time inferencing across computer vision, transformer models, and GenAI workloads.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003ePowered by MLSoC Modalix SoM\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003eThe MLSoC Modalix SoM combines the power and performance of Modalix with extended peripherals, all in a compact form factor designed to scale Physical AI deployments. Built on the field-proven MLSoC, Modalix, with its rich peripherals and unique architecture, delivers exceptional performance for multimodal Transformers, LLMs, LMMs, and GenAI workloads, while also supporting legacy CNN and computer vision algorithms.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eThe Modalix SoM offers the best-in-class performance per watt.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eDevelopment Flow\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003ePhase\u003c\/strong\u003e\u003c\/th\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eDescription\u003c\/strong\u003e\u003c\/th\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eDetails\u003c\/strong\u003e\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eEvaluate\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eUse Palette to compile and run models, assess performance (FPS, latency, compute utilization), and monitor system metrics.\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid #000; padding: 8px;\"\u003e\n\u003cul style=\"margin: 0; padding-left: 18px;\"\u003e\n\u003cli\u003eDocker-based toolchain\u003c\/li\u003e\n\u003cli\u003eARM cross-compiler\u003c\/li\u003e\n\u003cli\u003ePlatform image build \u0026amp; deploy tools\u003c\/li\u003e\n\u003cli\u003eIntegrated KPIs and performance feedback\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003ePrototype\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eDevelopers can rapidly prototype functional pipelines using SiMa.ai’s Python APIs.\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eEnables fast bring-up of custom ML workflows directly on the hardware without complex embedded optimization.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eDemonstrate\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eThe DevKit supports multi-camera input and high-speed interfaces for showcasing applications.\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid #000; padding: 8px;\"\u003e\n\u003cul style=\"margin: 0; padding-left: 18px;\"\u003e\n\u003cli\u003eMIPI CSI-2\u003c\/li\u003e\n\u003cli\u003eIP-based input\u003c\/li\u003e\n\u003cli\u003eUSB 3.2\u003c\/li\u003e\n\u003cli\u003eReal-time vision AI demo via HDMI with minimal latency\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eSpecifications\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eSubsystem\u003c\/strong\u003e\u003c\/th\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eSpecifications\u003c\/strong\u003e\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eMLSoC Modalix with ML Accelerator (MLA)\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e50 TOPs (BF16, INT8, INT16); supports GenAI and neural networks\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eApplication Processor\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e8× Arm Cortex-A65 @ 1.4–1.5 GHz; 32k Dhrystone MIPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eMemory\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e32 GB 128-bit LPDDR5, 128-bit @ 6400 Mbps\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eVideo Codec\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eH.264\/H.265\/AV1 Decode 4K@60; H.264\/H.265 Encode 4K@60\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eComputer Vision (CVU)\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e4-core Synopsys EV74 @ 1 GHz; 720 16-bit GOPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); 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padding: 8px; text-align: center;\"\u003e0–35°C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eAvailable Interfaces\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg alt=\"\" src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/Gemini_Generated_Image_7t3n4p7t3n4p7t3n.png?v=1763376133\"\u003e\u003c\/p\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%; height: 147.75px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 10.5938px;\"\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 10.5938px;\"\u003e\u003cstrong\u003eNo.\u003c\/strong\u003e\u003c\/th\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 10.5938px;\"\u003e\u003cstrong\u003eInterfaces\u003c\/strong\u003e\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003eHDMI 1.4 @ 4K\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e2\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e2 × MIPI CSI-2 Connectors\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e3\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003eM.2 M — 4× PCIe Gen4 RC\/EP\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e4\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e4× USB 3.2\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e5\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1× USB-C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e6\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1× Gigabit Ethernet\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e7\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003eI²C \/ UART \/ GPIO \/ SPI \/ GPIO\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eResources\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eProduct Brief\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003ca href=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/Modalix-DevKit-Product-Brief_03.1.pdf?v=1763376668\" rel=\"noopener\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eWhat’s Included\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003e• DevKit with enclosure\u003c\/strong\u003e (Modalix SoM and Carrier Board)\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003e• Universal power adaptor\u003c\/strong\u003e (DC 12V @ 5A)\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003e• M.2 500GB NVME storage\u003c\/strong\u003e\u003c\/p\u003e","brand":"SiMa.ai","offers":[{"title":"Default Title","offer_id":51001180094781,"sku":"SBC1144","price":149999.99,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/devkit-3-0_480x256_a69c6869-5027-45f2-92e6-1c0f93dfd6d4.webp?v=1774510820"},{"product_id":"sima-ai-modalix-deployment-kit","title":"SiMa.ai Modalix Deployment Kit  : (SW license extra)","description":"\u003ch2 style=\"text-align: center;\"\u003eModalix Deployment Kit\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003eThe SiMa.ai MLSoC Modalix Development Kit (DevKit) is a complete hardware and software platform for evaluating and prototyping intelligent Physical AI applications using the latest Modalix System-on-Module (SoM).\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eDesigned for rapid deployment, this kit enables seamless development, benchmarking, and proof-of-concept creation with SiMa.ai’s Palette software, offering best-in-class performance-per-watt in a compact form factor. Ideal for industrial, robotics, and vision-based and LLM-based applications, this kit supports real-time inferencing across computer vision, transformer models, and GenAI workloads.\u003c\/p\u003e\n\u003cdiv style=\"display: grid; grid-template-columns: 1fr; gap: 24px; margin-bottom: 24px;\"\u003e\n\u003c!-- Cards Container --\u003e\n\u003cdiv class=\"feature-grid\"\u003e\n\u003cdiv class=\"card\"\u003e\n\u003ch3\u003eBuild, test, and deploy AI apps fast\u003c\/h3\u003e\n\u003cp\u003eLaunch edge AI applications in just minutes with our streamlined workflow\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"card\"\u003e\n\u003ch3\u003ePrototype smart, autonomous systems\u003c\/h3\u003e\n\u003cp\u003eDesign Physical AI, robotics, and sensor-based apps with ease\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"card\"\u003e\n\u003ch3\u003eExplore demos, models, and docs\u003c\/h3\u003e\n\u003cp\u003eAccess ready-to-run examples, pretrained models, and full guides\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"card\"\u003e\n\u003ch3\u003eComplete kit with all essentials\u003c\/h3\u003e\n\u003cp\u003eFast deployment includes software, cables, tools, and power—no extras needed\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"card\"\u003e\n\u003ch3\u003eDeploy your models seamlessly with industry-standard compatibility\u003c\/h3\u003e\n\u003cp\u003eDeploy your models seamlessly with industry-standard compatibility\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cstyle\u003e\n.feature-grid {\n  display: grid;\n  gap: 24px;\n  grid-template-columns: repeat(1, 1fr);\n}\n\n\/* Tablet *\/\n@media (min-width: 768px) {\n  .feature-grid {\n    grid-template-columns: repeat(2, 1fr);\n  }\n}\n\n\/* Desktop *\/\n@media (min-width: 1024px) {\n  .feature-grid {\n    grid-template-columns: repeat(5, 1fr);\n  }\n}\n\n.card {\n  background: #fff;\n  border-radius: 16px;\n  padding: 32px 24px;\n  text-align: center;\n  box-shadow: 0 8px 24px rgba(0,0,0,0.08);\n}\n\n.card h3 {\n  margin-bottom: 12px;\n}\n\n.card p {\n  margin: 0;\n}\n\u003c\/style\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003ePowered by MLSoC Modalix SoM\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003eThe MLSoC Modalix System-on-Module (SoM) provides the proven performance of the Modalix MLSoC architecture in a compact, deployment-ready form factor, purpose-built to Scale Physical AI applications.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eThe Modalix innovative system architecture seamlessly integrates a set of compute engines and peripherals, delivering best-in-class performance per watt for advanced workloads, including multimodal Transformers, Large Language Models (LLMs), Large Multimodal Models (LMMs), and Generative AI (GenAI). It also maintains full support for legacy convolutional neural networks (CNNs) and traditional\u003cbr\u003ecomputer vision algorithms, ensuring broad compatibility across both modern and established ML pipelines.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003eThe Modalix SoM offers the best-in-class performance per watt.\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg alt=\"\" src=\"https:\/\/sima.ai\/wp-content\/uploads\/2025\/08\/som-chips-with-bg.png\" class=\"object-contain\" decoding=\"async\"\u003e\u003c\/p\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eMLSoC Modalix SoM Feature Highlights\u003cbr\u003e\n\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eMachine Learning Accelerator (MLA)\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003e50 TOPs (BF16, INT8, INT16)\u003cbr\u003eSupports LLMs, neural networks, and GenAI\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eApplication Compute Unit (ACU)\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003e8 × ARM Cortex-A65 @ 1.4 GHz\u003cbr\u003e32K Dhrystone MIPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eMemory\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003e32 GB or 8 GB on-board 128-bit LPDDR5 (6400 Mbps) system memory\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eBoot and Security Unit (BSU)\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003eSecure boot with boot code authentication and encryption\u003cbr\u003eSecure key storage and management\u003cbr\u003eSecurity engine for user code\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eVideo Codec\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003eDecode H.264 \/ H.265 \/ AV1 up to 4K60\u003cbr\u003eEncode H.264 \/ H.265 up to 4K60\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eComputer Vision Unit (CVU)\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003e4-core Synopsys EV74 DSP @ 1 GHz\u003cbr\u003e720 GOPS (16-bit)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eLow-Latency ISP\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003eARM Mali-C-1 @ 1.2 GHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eDisplay Connectivity\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003eHDMI 1.4 port with 4K resolution\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003ePeripherals\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003e4 × 2-lane MIPI CSI-2\u003cbr\u003e4 × PCIe Gen5 RC \u0026amp; EP\u003cbr\u003e1 × 1Gb Ethernet PHY\u003cbr\u003e3 × USB 3.0\u003cbr\u003e4 × I2C, 3 × UART, 14 × GPIO\u003cbr\u003e2 × SPI\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eStorage\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003eExternal NVMe via PCIe x4\u003cbr\u003eExternal SSD via USB 3.0\u003cbr\u003e16 GB eMMC flash\u003cbr\u003e64 MB QSPI flash\u003cbr\u003e128 KB EEPROM\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003ePower Supply\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003eFlexible 5–20 V power input\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eForm Factor\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003e69.6 mm × 45 mm\u003cbr\u003e260-pin SO-DIMM connector\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 50.7592%;\"\u003e\u003cstrong\u003eOperating Temperature\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; width: 49.2408%;\"\u003e\n\u003cstrong\u003eCommercial SoM: \u003c\/strong\u003e 0°C to +60°C\u003cbr\u003e\u003cstrong\u003e    Industrial SoM:  \u003c\/strong\u003e-40°C to +85°C\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eDevelopment Flow\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003ePhase\u003c\/strong\u003e\u003c\/th\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eDescription\u003c\/strong\u003e\u003c\/th\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eDetails\u003c\/strong\u003e\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eEvaluate\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eUse Palette to compile and run models, assess performance (FPS, latency, compute utilization), and monitor system metrics.\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid #000; padding: 8px;\"\u003e\n\u003cul style=\"margin: 0; padding-left: 18px;\"\u003e\n\u003cli\u003eDocker-based toolchain\u003c\/li\u003e\n\u003cli\u003eARM cross-compiler\u003c\/li\u003e\n\u003cli\u003ePlatform image build \u0026amp; deploy tools\u003c\/li\u003e\n\u003cli\u003eIntegrated KPIs and performance feedback\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003ePrototype\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eDevelopers can rapidly prototype functional pipelines using SiMa.ai’s Python APIs.\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eEnables fast bring-up of custom ML workflows directly on the hardware without complex embedded optimization.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cstrong\u003eDemonstrate\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eThe Deployment supports multi-camera input and high-speed interfaces for showcasing applications.\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid #000; padding: 8px;\"\u003e\n\u003cul style=\"margin: 0; padding-left: 18px;\"\u003e\n\u003cli\u003eMIPI CSI-2\u003c\/li\u003e\n\u003cli\u003eIP-based input\u003c\/li\u003e\n\u003cli\u003eUSB 3.2\u003c\/li\u003e\n\u003cli\u003eReal-time vision AI demo via HDMI with minimal latency\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eAvailable Interfaces\u003c\/h2\u003e\n\u003cp style=\"text-align: center;\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/Gemini_Generated_Image_7t3n4p7t3n4p7t3n.png?v=1763376133\" alt=\"\"\u003e\u003c\/p\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%; height: 147.75px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 10.5938px;\"\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 10.5938px;\"\u003e\u003cstrong\u003eNo.\u003c\/strong\u003e\u003c\/th\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 10.5938px;\"\u003e\u003cstrong\u003eInterfaces\u003c\/strong\u003e\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003eHDMI 1.4 @ 4K\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e2\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e2 × MIPI CSI-2 Connectors\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e3\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003eM.2 M — 4× PCIe Gen4 RC\/EP\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e4\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e4× USB 3.2\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e5\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1× USB-C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e6\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1× Gigabit Ethernet\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e7\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003eI²C \/ UART \/ GPIO \/ SPI \/ GPIO\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eResources\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003eProduct Brief\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center;\"\u003e\u003cspan style=\"color: rgb(255, 42, 0);\"\u003e\u003ca href=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/Modalix-SoM-Product-Brief_05.3.pdf?v=1770721342\" style=\"color: rgb(255, 42, 0);\" rel=\"noopener\" target=\"_blank\"\u003eDownload\u003c\/a\u003e\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"text-align: center;\"\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eWhat’s Included\u003cstrong\u003e\u003c\/strong\u003e\n\u003c\/h2\u003e\n\u003ctable style=\"border-collapse: collapse; width: 100%; height: 147.75px;\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 10.5938px;\"\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 10.5938px;\"\u003e\u003cstrong\u003eParts\u003c\/strong\u003e\u003c\/th\u003e\n\u003cth style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 10.5938px;\"\u003e\u003cstrong\u003eQuantity\u003c\/strong\u003e\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003eModalix SoM 32GB \u003cspan style=\"color: rgb(255, 42, 0);\"\u003e(Commercial\/Industrial)\u003c\/span\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003eCarrier Board\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003eActive Heatsink\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003eM.2 240GB NVME Solid State Drive\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e12V\/5A Power Supply\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"height: 19.5938px;\"\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003eMetal Enclosure\u003c\/td\u003e\n\u003ctd style=\"border: 1px solid rgb(0, 0, 0); padding: 8px; text-align: center; height: 19.5938px;\"\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003ch2 style=\"text-align: center;\"\u003eVideos\u003c\/h2\u003e\n\u003cdiv style=\"position: relative; width: 100%; padding-top: 56.25%; background: #000;\"\u003e\u003cvideo preload=\"metadata\" playsinline=\"\" controls=\"controls\" style=\"position: absolute; top: 0; left: 0; width: 100%; height: 100%; object-fit: contain;\"\u003e\n    \u003csource type=\"video\/mp4\" src=\"https:\/\/cdn.shopify.com\/videos\/c\/o\/v\/82949aeb6dc7480ba08a1f4e08efa396.mp4\"\u003e\n    Your browser does not support the video tag.\n  \u003c\/source\u003e\u003c\/video\u003e\u003c\/div\u003e","brand":"SiMa.ai","offers":[{"title":"Commercial","offer_id":51369869181245,"sku":"SBC1158","price":84999.99,"currency_code":"INR","in_stock":true},{"title":"Industrial","offer_id":51369869214013,"sku":"SBC1159","price":89999.99,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/files\/devkit-3-0_480x256_a69c6869-5027-45f2-92e6-1c0f93dfd6d4.webp?v=1774510820"}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0014\/4313\/5560\/collections\/SiMa.ai-logo.jpg?v=1785995989","url":"https:\/\/thinkrobotics.com\/collections\/sima-ai-official-page.oembed","provider":"ThinkRobotics.com","version":"1.0","type":"link"}