Akamai expands its AI Cloud platform with dedicated inference and agent execution environments

Akamai expands its AI Cloud platform with dedicated inference and agent execution environments

Akamai Technologies Inc. is expanding its AI Cloud infrastructure platform with a pair of new foundational components called Akamai Inference and Akamai Agent Sandbox.

They provide its enterprise customers with a highly customizable managed environment from which they can serve and execute artificial intelligence workloads and agents on any infrastructure, from its cloud data centers to the network edge.

The company says it’s addressing the growing enterprise demand for more flexible yet reliable serving infrastructure and a way to integrate AI with proprietary and third-party data sources with strict governance protocols. As autonomous AI agents take on more software coding responsibilities, organizations also need harder boundaries to secure those systems.

The Akamai AI Cloud aims to provide all of that, and more, offering customers everything they need to get their AI workloads and agents up and running: compute, cloud storage, networking and security. It also offers a vast choice of graphics processing units and other AI accelerators available from more than 4,350 edge locations. The Akamai Cloud platform sits at the heart of the company’s AI strategy, which envisions AI inference running closer to end users and the data it needs in order to minimize latency.

Given its ambitious goals, the launch of Akamai Inference is a big deal. Akamai said it’s a managed service offering that provides customers with access to dozens of open-weight and custom AI models through OpenAI-compatible application programming interfaces. The main advantage of Akamai Inference is that it allows teams to deploy new AI applications and agents at the edge without rewriting any code.

At launch, enterprises will be able to choose from 12 open-weight models ranging from 8 billion to 2.8 trillion parameters, including Nvidia Corp.’s Nemotron 3 Ultra, OpenAI Group PBC’s gpt-oss-120b and Google LLC’s Gemma 4. There’s also a selection of specialized “embedding” models for retrieval-augmented generation pipelines. These are meant to connect the open-weight models with Akamai’s managed database services to ensure their responses are grounded in enterprise data.

The Akamai Agent Sandbox, meanwhile, is all about secure execution. It’s an isolated execution space for running AI agents that work autonomously on behalf of human users. Within the sandbox, AI agents run on Akamai Functions, with their code contained in isolated WebAssembly environments managed by the open-source Spin framework. With these sandboxes, enterprises will be able to enforce granular control over everything from the agent’s compute and memory to their system APIs and outbound network access, ensuring they never overstep their boundaries.

Adam Karon, chief operating officer and general manager of Akamai Cloud, said the company believes inference is going to become the main focus for the vast majority of enterprises in future. “Our customers have already proved that thesis,” he said. “They want to build, run and protect AI on the same platform. Akamai Inference and Akamai Sandbox add the inference and execution layers that turn our AI infrastructure into a full AI stack, and our security portfolio protects every layer of it.”

The company is also keen to give customers more choice over the hardware they use to power their AI workloads, which is why it also revealed it’s expanding its fleet of GPU platforms within Akamai AI Cloud. It now offers access to Nvidia Blackwell Ultra clusters, in particular RTX PRO 6000 Blackwell Server Edition GPUs. Each eight-GPU Blackwell Ultra node provides up to 2.3 terabytes of total HBM3e memory, enabling support for long-context reasoning, Akamai said.

Akamai is also planning to expand its fleet further with Nvidia’s next-generation Vera Rubin GPU platform, which will be made available in the new year, it said.

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