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Top AI Performance Starts on a Cloud Built for Speed

Accelerate inference, lower costs, and scale AI apps everywhere

Are centralized clouds slowing down your AI app performance? Move AI workloads to the cloud built for speed.

Akamai Cloud delivers GPU-powered AI inference on a globally distributed infrastructure, giving you the real-time AI performance you need to compete. Build, deploy, and scale AI applications faster on our open, developer-friendly platform, with predictable pricing and integrated security.

Real-time app experiences demand ultra-fast AI inference at the edge. Akamai Cloud is already there.

Decentralized compute removes the physical distance between your models and your users, so your apps deliver faster responses.  

GPUs on a distributed cloud

Powerful NVIDIA Blackwell GPUs on our distributed infrastructure deliver real-time AI performance.

Ultra-fast AI inference

Achieve sub–50-ms latency and 3x better throughput for agents by eliminating the lag of centralized clouds.

Built-in security at scale

Defend against prompt injection and data exfiltration with built-in Zero Trust security and DDoS protection.

Proven results

Deploy on a distributed cloud to reduce latency by up to 60%, while also achieving significant cost savings.

The State of AI Inference: 50% of AI fails at peak load

Discover the data behind the latency wall and how organizations use distributed compute to scale production AI ROI.

New AI survey: Inference breaks the latency wall
New AI survey: Inference breaks the latency wall

The State of AI Inference: 50% of AI fails at peak load

Discover the data behind the latency wall and how organizations use distributed compute to scale production AI ROI.

Customer Stories

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Myota

See how Myota escaped cloud constraints and delivered secure, always-available storage on Akamai’s open cloud architecture.

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Ceeblue

Live-streaming pioneer Ceeblue optimized ultra-low-latency streaming for live sports and betting on Akamai’s global infrastructure.

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ConvoBot AI Transformed Operations with Akamai

ConvoBot AI reduced infrastructure costs by 45% while improving reliability and support with Akamai’s cloud computing services.

Resources

State of AI Inference: The Third Wave

As AI scales, centralized clouds alone can’t meet latency and reliability demands — teams are shifting to distributed architectures.

How Harmonic Proved High-Performance AI Inference on Akamai GPUs

Harmonic uses Akamai’s edge GPUs to deliver real-time 8K video, achieving a 60% reduction in latency and 86% lower costs.

The AI Leader’s Playbook

This infographic provides a strategic roadmap for the 74% of enterprises that measure the success of AI through higher revenue.

Frequently Asked Questions (FAQ)

Frequently Asked Questions (FAQ)

Most traditional cloud architecture is centralized, meaning it relies on a few massive data centers located far away from the average user. When an AI app is centralized, every request must travel hundreds or thousands of miles and back again. This long-haul trip creates physical latency. For real-time applications like voice assistants or chatbots, even a 100-ms delay can make the interaction feel disjointed and un-human.  

Actually, it usually lowers them. Centralized clouds often charge heavy egress fees to move data out of their ecosystem. Edge architecture minimizes these costs compared to legacy cloud providers.

Yes. Akamai provides the flexibility to run any model size, from fine-tuning specialized versions to building dedicated custom clusters designed for large-scale workloads.

Security is baked into our distributed fabric. Because inference happens closer to the user, sensitive data often doesn’t need to travel across the public internet to a distant data center. We layer this with AI-native DDoS protection and Zero Trust security to protect both your models and your users.

Centralized clouds aren’t ideal for real-time AI. Innovation is vital to move GPU power close to users, enabling millisecond responses and ensuring that high-performance scaling remains fast, secure, and cost-effective.