Akamai Technologies (NASDAQ: AKAM) has officially launched Akamai Inference Cloud, a groundbreaking distributed AI platform designed to move AI inference from centralized data centers to the edge of the internet. The move positions Akamai as a key player in reshaping how generative and agentic AI systems operate in real-world, real-time environments.
Built on NVIDIA’s Blackwell AI infrastructure, Akamai Inference Cloud combines accelerated computing, distributed edge architecture, and intelligent orchestration to deliver low-latency, high-performance inference closer to users, devices, and data sources.
The Next Frontier: Agentic AI at the Edge
The new platform marks a shift toward what Akamai calls “agentic AI” — intelligent systems that act autonomously, reason in real time, and adapt to local context. With over 4,200 distributed edge locations worldwide, Akamai aims to make AI decision-making as geographically ubiquitous and responsive as the web itself.
“The next wave of AI requires the same proximity to users that allowed the internet to scale,” said Dr. Tom Leighton, Akamai’s CEO and co-founder. “Akamai solved this challenge before — and we’re doing it again. Powered by NVIDIA AI infrastructure, Akamai Inference Cloud will meet the intensifying demand to scale AI inference capacity and performance by putting AI’s decision-making in thousands of locations around the world.”
NVIDIA founder and CEO Jensen Huang echoed this vision: “Inference has become the most compute-intensive phase of AI — demanding real-time reasoning at planetary scale. Together, NVIDIA and Akamai are moving inference closer to users everywhere, unlocking the next generation of intelligent applications.”
Inside the Akamai Inference Cloud
Akamai’s new platform brings together:
- NVIDIA RTX PRO Servers, powered by RTX 6000 Blackwell GPUs and BlueField-3 DPUs, soon to integrate the BlueField-4 for accelerated and secure data access.
- NVIDIA AI Enterprise software, including NIM microservices, enabling instant model execution at the edge.
- Akamai’s distributed cloud infrastructure, spanning thousands of global edge points.
This combination creates a real-time, generative edge computing fabric that supports everything from conversational agents to physical AI systems like autonomous vehicles and industrial robotics.
Key Capabilities of Akamai Inference Cloud
- Extending AI Factories to the Edge – Traditional AI factories centralize data and model training. Akamai extends these capabilities outward, decentralizing inference and allowing smart agents to adapt to user context, intent, and location in milliseconds.
- Streaming Inference for Financial and Decision Systems – Many AI agents require multiple sequential inferences. Akamai’s edge-native architecture eliminates network lag, enabling real-time fraud detection, instant financial insights, and responsive industrial automation.
- Real-Time Physical AI – Designed for autonomous systems, the Inference Cloud supports millisecond-level decision-making, essential for safety-critical applications like factory robotics, autonomous transport, and surgical robotics.
- Accelerated Time-to-Value – The platform’s intelligent orchestration layer automatically routes workloads between the edge and central AI factories, balancing speed and complexity while abstracting infrastructure management for developers and enterprises.
Why It Matters
AI inference — the process of applying trained models to generate results — has become the most resource-intensive and latency-sensitive phase of AI operations. As models grow more complex and user interactions demand instant responses, pushing inference to the edge is becoming an architectural necessity.
With Akamai Inference Cloud, the company is leveraging decades of experience in global content delivery and web acceleration to redefine how and where AI operates — turning the internet itself into an intelligent, responsive computational network.
This strategic collaboration with NVIDIA also underscores a broader industry trend: AI infrastructure moving out of centralized data silos and into distributed, intelligent networks capable of powering the next wave of real-time, context-aware AI experiences.
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