NVIDIA Metropolis
Discover this advanced collection of developer workflows and tools to build, deploy, and scale vision AI and generative AI from the edge to the cloud. It delivers exceptional scale, throughput, cost-effectiveness, and faster time to production.
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Explore All the Benefits
Faster Builds
Use and tune high-performance pretrained models to streamline AI training for your unique industry. Use our cloud-native modular microservices and reference applications to accelerate development.
Lower Cost
Powerful SDKs—including NVIDIA TensorRT™, DeepStream, and TAO Toolkit—reduce overall solution cost by maximizing inference throughput and optimizing hardware usage on NVIDIA platforms and infrastructure.
Flexible Deployments
Deploy with flexibility using cloud-native Metropolis microservices and containerized apps offering options for on-premises, cloud, or hybrid deployments.
Enhance Your Applications With Generative AI
Retrieval Augmented Generation (RAG) Workflow
This suite of customizable, cloud-native building blocks is ideal for developing generative AI applications. The workflows let you accelerate development of generative AI applications by seamlessly integrating Large Language Models (LLM) with enterprise data.
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NVIDIA Visual Insight Agent (VIA)
NVIDIA VIA is a collection of workflows to build AI agents capable of processing large amounts of live or archived videos and images with Vision-Language Models (VLM) - whether deployed at the edge or cloud. This new generation of visual AI agents will help nearly every industry summarize, search, and extract actionable insights from video using natural language.
Learn More About VIA Sign Up for Early Access
Metropolis APIs and Microservices
With the rapidly evolving AI landscape, developers building vision AI applications for the edge are challenged by more complex and longer development cycles. NVIDIA Metropolis offers a collection of powerful APIs and microservices for developers to easily develop and deploy applications on the edge to any cloud.
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Powerful Tools for
AI-Enabled Video Analytics
The Metropolis suite of SDKs provides a variety of starting points for AI application development and deployment.
NVIDIA Omniverse™ Replicator
Generate physically accurate 3D synthetic data at scale, or build your own synthetic data tools and frameworks. Bootstrap perception AI model training and achieve accurate Sim2Real performance without having to manually curate and label real-world data.
Learn More About Omniverse Replicator
Also check out Omni.Replicator.Character, an Isaac Sim extension using Replicator that focuses on simulation and synthetic data generation (SDG) of agent movement—such as from people and an Autonomous Mobile Robot (AMR)—using a high-level user interface.
Learn More About Omniverse Replicator
Pretrained Models
Eliminate the time-consuming process of building models from scratch. Choose from over 100+ permutations of highly accurate models and generic neural network architectures or start with our task-based models to recognize human actions and poses, detect people in crowded spaces, classify vehicles and license plates, and much more.
Learn More About Pretrained AI Models Try Pretrained Models With Jupyter Notebook
TAO Toolkit
The Train, Adapt, and Optimize (TAO) Toolkit is a low-code AI model development solution that lets you use the power of transfer learning to fine-tune NVIDIA pretrained models with your own data and optimize for inference—without AI expertise or a large training dataset.
Learn More About TAO Toolkit Try TAO on LaunchPad
Many AI Model Frameworks
Create your AI models and applications on these popular NVIDIA-supported AI frameworks. Integrate any existing AI model into the Metropolis workflow and easily customize existing models in TensorFlow, PyTorch, and more by easily converting to TAO.
Learn More About Deep Learning Frameworks
TensorRT
This SDK for high-performance deep learning inference includes an inference optimizer and runtime that delivers low latency and high throughput, both on edge devices and within the cloud. TensorRT is supported on all popular frameworks, including TensorFlow and PyTorch. Powering NVIDIA solutions such as NVIDIA JetPack™ and DeepStream, TensorRT give you a gateway to accelerated inferencing.
Learn More About TensorRT
DeepStream SDK
NVIDIA DeepStream SDK is a complete streaming analytics toolkit based on GStreamer for AI-based multi-sensor processing, video, audio, and image understanding. It’s ideal for vision AI developers, software partners, startups, and OEMs building IVA apps and services.
Learn More About DeepStream SDK Try DeepStream on LaunchPad
Triton Inference Server
The NVIDIA Triton™ open-source, multi-framework inference serves software to deploy, run, and scale AI models in production on both GPUs and CPUs. It supports all major frameworks, including TensorFlow and Pytorch, and maximizes inference throughput on any platform.
Learn More About Triton Inference Server
Video Storage Toolkit (VST)
Easily manage and store footage for large volumes of video cameras with hardware-accelerated video decoding, streaming, and storage. Get started quickly with the included web-based user interface and take advantage of VST flexibility through intuitive REST APIs. It’s available for NVIDIA Jetson Xavier™ and Orin™ devices.
Learn More About VST
Metropolis Microservices
This suite of cloud-native microservices and reference applications fast-tracks development and deployment of vision AI applications. Unlock business insights for a wide range of spaces, ranging from roadways to airports to retail stores, in significantly shortened development cycles.
Learn More About Metropolis microservices
CUDA-X Libraries
Take advantage of low-level libraries and primitives for computer vision and more that can help with pre-processing and model performance. NVIDIA® CUDA-X™, built on top of NVIDIA CUDA®, is a collection of libraries, tools, and technologies that deliver dramatically higher performance in compute-intensive algorithms spanning complex math, deep learning, and image processing.
Cloud Containers
Containerize your applications easily with Docker, Kubernetes, and GPU Operators to deploy cloud-native solutions on Jetson, x86, and dGPU. Or use pre-built cloud-native Metropolis microservices.
Learn More About Cloud Containers
Generate – Synthetic Data Generation
NVIDIA Omniverse™ Replicator
Generate physically accurate 3D synthetic data at scale, or build your own synthetic data tools and frameworks. Bootstrap perception AI model training and achieve accurate Sim2Real performance without having to manually curate and label real-world data.
Learn More About Omniverse Replicator
Also check out Omni.Replicator.Character, an Isaac Sim extension using Replicator that focuses on simulation and synthetic data generation (SDG) of agent movement—such as from people and an Autonomous Mobile Robot (AMR)—using a high-level user interface.
Learn More About Omniverse Replicator
Train – Application-Specific Model Customization
Pretrained models
Eliminate the time-consuming process of building models from scratch. Choose from over 100+ permutations of highly accurate models and generic neural network architectures or start with our task-based models to recognize human actions and poses, detect people in crowded spaces, classify vehicles and license plates, and much more.
Learn More About Pretrained AI Models Try Pretrained Models With Jupyter Notebook
TAO Toolkit
The Train, Adapt and Optimize (TAO) Toolkit is a low-code AI model development solution that lets you use the power of transfer learning to fine-tune NVIDIA pretrained models with your own data and optimize for inference–without AI expertise or a large training dataset.
Learn More About TAO Toolkit Try TAO on LaunchPad
Many AI model frameworks
Create your AI models and applications on these popular NVIDIA-supported AI frameworks. Integrate any existing AI model into the Metropolis workflow and easily customize existing models in TensorFlow, PyTorch, and more by easily converting to TAO.
Learn More About Deep Learning Frameworks
Build – Powerful AI applications
TensorRT
This SDK for high-performance deep learning inference includes an inference optimizer and runtime that delivers low latency and high throughput, both on edge devices and within the cloud. TensorRT is supported on all popular frameworks, including TensorFlow and PyTorch. Powering NVIDIA solutions such as JetPack™ and DeepStream, TensorRT is a gateway to accelerated inferencing.
Learn More About TensorRT
DeepStream SDK
NVIDIA DeepStream SDK is a complete streaming analytics toolkit based on GStreamer for AI-based multi-sensor processing, video, audio, and image understanding. It’s ideal for vision AI developers, software partners, startups, and OEMs building IVA apps and services.
Learn More About DeepStream SDK Try DeepStream on LaunchPad
Triton Inference Server
The NVIDIA Triton™ open-source, multi-framework inference serves software to deploy, run, and scale AI models in production on both GPUs and CPUs. It supports all major frameworks, including TensorFlow and Pytorch, and maximizes inference throughput on any platform.
Learn More About Triton Inference Server
Video Storage Toolkit (VST)
Easily manage and store footage for large volumes of video cameras with hardware-accelerated video decoding, streaming, and storage. Get started quickly with the included web-based user interface and take advantage of VST flexibility through intuitive REST APIs. It’s available for NVIDIA Jetson Xavier™ and Orin™ devices.
Learn More About VST
Metropolis Microservices
This suite of cloud-native microservices and reference applications fast-tracks development and deployment of vision AI applications. Unlock business insights for a wide range of spaces, ranging from roadways to airports to retail stores, in significantly shortened development cycles.
Learn More About Metropolis microservices
CUDA-X libraries
Take advantage of low-level libraries and primitives for computer vision and more that can help with pre-processing and model performance. NVIDIA® CUDA-X™, built on top of NVIDIA CUDA®, is a collection of libraries, tools, and technologies that deliver dramatically higher performance in compute-intensive algorithms spanning complex math, deep learning, and image processing.
Deploy – Application Management and Scaling
Cloud containers
Containerize your applications easily with Docker, Kubernetes, and GPU Operators to deploy cloud-native solutions on Jetson, x86, and dGPU. Or use pre-built cloud-native Metropolis microservices.
Learn More About Cloud Containers
Get Started With Sample Applications
Generative AI at the Edge
Learn how to bring generative AI applications into production faster with Metropolis microservices for Jetson.
Vision AI Applications With APIs
Learn how to build vision AI applications using APIs provided by Metropolis microservices for Jetson.
Defect Detection
Learn how to transform industrial defect detection with NVIDIA TAO and vision AI models.
Character Detection and Recognition
Learn how to train and deploy character detection and recognition models with NVIDIA TAO and Triton™.
View all Metropolis technical blogs
Explore NVIDIA GTC Talks On-Demand
Develop, deploy, and scale AI-enabled video analytics applications with NVIDIA Metropolis.