USE CASE
Run AI at the Edge
Streamline and secure how artificial intelligence (AI) models and applications are deployed, secured, monitored, and managed in remote edge environments.
Accelerate and Scale Edge AI Deployments
Deploy Across Tens of Thousands of Locations
Effortlessly scale AI workloads across geographically distributed edge deployments.
Zero-Trust Security
Hardware-based security protects devices and data in the field.
Monitor and Manage With Less Effort
Simplify monitoring and application lifecycle management through remote orchestration.
Reduce Costs
Eliminate vendor lock-in with an open hardware ecosystem.
Why Run AI at the Edge
Edge AI is rapidly becoming essential across industries, allowing organizations to automate local real time decision making and alleviate reliance on cloud infrastructure. Edge AI improves operational efficiency, and reduces costs while enabling AI-driven analytics, predictive insights, and improving customer experience. For many use cases, AI will move closer to the data, driven by the need for real-time decision making and operational efficiency. According to Gartner, by 2029, at least 60% of edge computing deployments will use composite AI (both predictive and generative AI [GenAI]), compared to less than 5% in 2023.
How ZEDEDA Helps You With Edge AI
Unlock the power of distributed AI with ZEDEDA. Seamlessly deploy and manage edge AI models and applications across thousands of locations, eliminating manual processes with automated provisioning and pre-configured solutions. Secure your deployments with a robust Zero Trust architecture, protecting your data and IP. Effortlessly monitor device health and manage your entire edge infrastructure from a single pane of glass, reducing costs with flexible hardware and connectivity support.
Deploy Edge AI Models and Applications Across Tens of Thousands of Locations
- Eliminate manual processes with pre-configured software and hardware to reduce deployment time.
- Reduce deployment time with automated provisioning and configuration of devices.
- Deploy and manage devices remotely from a single location.
- Handle large deployments with scalable architecture supporting thousands of distributed edge nodes.
Protect Edge AI Models and Applications with Zero Trust Security
- Zero Trust security model protects against cyber threats.
- Protect against unauthorized access and tamper with measure boot and remote attestation. Protect IP from tampering or theft.
- Protect data and communications with secure communication channels and data encryption, in-flight and at rest.
Monitor and Manage Edge AI Models and Applications With Less Effort
- Ensure device health through real-time monitoring and health checks.
- Manage all edge devices from a single pane of glass.
- Simplify software maintenance with automated software updates and patching.
- Manage distributed systems effectively with centralized management and orchestration capabilities.
Reduce Edge AI Costs With Diverse Hardware and Connectivity Support
- Lower deployment costs and simplify management by abstracting heterogeneous and constrained hardware.
- Support and share GPUs, including NVIDIA Jetson-based hardware.
- Enable diverse connectivity options, e.g., 2G, 4G, 5G, cable, satellite, and microwave.
How to Build and Deploy Scalable Edge AI with ZEDEDA and NVIDIA
Watch how ZEDEDA offers a complete end-to-end edge AI workflow, integrating NVIDIA’s TAO Toolkit, the NGC catalog, and other AI tools to simplify model development, optimization, and deployment. In this demo, discover how to use NVIDIA’s pre-trained models from the NGC catalog, optimize them with the TAO Toolkit, and accelerate on NVIDIA Jetson devices with TensorRT. We also demonstrate how to monitor AI models at scale using Grafana and Prometheus for real-time performance tracking. Perfect for those interested in Edge AI, NVIDIA Jetson, NGC, TensorRT, Grafana, Prometheus, and ZEDEDA.
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