Datasheet:

As AI adoption accelerates, businesses are moving away from centralized cloud-based processing and turning to Edge Computing to deploy AI models closer to where data is generated. This shift is driven by the need for low-latency decision-making, real-time analytics, and reduced cloud dependency, especially in industries like smart cities, retail, industrial automation, and telecommunications. However, managing thousands of distributed GPU-powered Edge AI devices presents significant challenges: scalability, security, remote monitoring, and efficient AI orchestration. Unlike traditional IT infrastructure, Edge AI deployments require continuous updates, real-time observability, and seamless workload distribution across decentralized locations—all without relying on highly skilled on-site technicians. Without an intelligent orchestration layer, companies struggle to scale their AI solutions efficiently, leading to costly manual interventions, security risks, and operational bottlenecks. Namla provides a cloud-native orchestration platform that streamlines Edge AI management, ensuring rapid deployment, effortless scaling, and robust security. Hardware-agnostic by design, Namla leverages Kubernetes for seamless orchestration across diverse Edge AI devices, including Nvidia Jetson and other hardware, ensuring maximum flexibility and scalability. Additionally, Namla integrates SD-WAN network capabilities, delivering secure, high-performance, and reliable Edge-to-Cloud connectivity across distributed infrastructures.

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