2 Integrations with NVIDIA Metropolis
View a list of NVIDIA Metropolis integrations and software that integrates with NVIDIA Metropolis below. Compare the best NVIDIA Metropolis integrations as well as features, ratings, user reviews, and pricing of software that integrates with NVIDIA Metropolis. Here are the current NVIDIA Metropolis integrations in 2026:
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NVIDIA Jetson
NVIDIA
NVIDIA's Jetson platform is a leading solution for embedded AI computing, utilized by professional developers to create breakthrough AI products across various industries, as well as by students and enthusiasts for hands-on AI learning and innovative projects. The platform comprises small, power-efficient production modules and developer kits, offering a comprehensive AI software stack for high-performance acceleration. This enables the deployment of generative AI at the edge, supporting applications like NVIDIA Metropolis and the Isaac platform. The Jetson family includes a range of modules tailored to different performance and power efficiency needs, such as the Jetson Nano, Jetson TX2, Jetson Xavier NX, and the Jetson Orin series. Each module is designed to meet specific AI computing requirements, from entry-level projects to advanced robotics and industrial applications. -
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NVIDIA DeepStream SDK
NVIDIA
NVIDIA's DeepStream SDK is a comprehensive streaming analytics toolkit based on GStreamer, designed for AI-based multi-sensor processing, including video, audio, and image understanding. It enables developers to create stream-processing pipelines that incorporate neural networks and complex tasks like tracking, video encoding/decoding, and rendering, facilitating real-time analytics on various data types. DeepStream is integral to NVIDIA Metropolis, a platform for building end-to-end services that transform pixel and sensor data into actionable insights. The SDK offers a powerful and flexible environment suitable for a wide range of industries, supporting multiple programming options such as C/C++, Python, and Graph Composer's intuitive UI. It allows for real-time insights by understanding rich, multi-modal sensor data at the edge and supports managed AI services through deployment in cloud-native containers orchestrated with Kubernetes.
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