Cloud Computing

In just a short time, we’ve seen AI transition from simple chat interfaces to autonomous agents capable of function calling, code execution, and persistent terminal use. But to orchestrate these capabilities securely, agents need more than just intelligence — they need a robust, hyper-scalable, secure compute environment in which to execute code. Since our preview

This is a new era — the agentic era – and the question is no longer, “what’s possible?” but rather, “what creates impact?” Today, organizations across industries around the world are swiftly moving from AI exploration and pilots to real-world use cases that drive impact, at scale. They are doing this with agents. In order

At Google I/O, we introduced a unified development toolkit featuring Antigravity 2.0 and the Managed Agents API, giving developers better ways to build locally and deploy securely to the cloud on a shared protocol layer. In this blog, we’re going to show you how Gemini Enterprise Agent Platform and the new developer tools shared at

At Google Cloud Next ‘26, we unveiled the blueprint for the Agentic Enterprise, sharing our eighth-generation TPUs, Gemini Enterprise Agent Platform, a fully reimagined Agentic Data Cloud, Workspace Intelligence, and security built for the AI era.  Today at Google I/O, we’re delivering a new set of powerful AI innovations and models — and putting them

The modern software development landscape isn’t happening just on one surface — it’s happening across an entire ecosystem of agentic tools. Agents are being developed at an unprecedented scale, and these agents require direct access to enterprise data for context and grounding. However, the current tooling for building agents and managing data is heavily fragmented.

In the mining industry, accurate geological analysis is required for improving mine design and development. Traditionally, this involved labor-intensive and time-consuming on-site inspections of drill core samples, often conducted in remote and challenging environments. ALS GeoAnalytics has streamlined this process through its LITHOLENS platform, a machine learning (ML)-powered system that uses deep learning and machine

Synthesia, an enterprise-focused AI video platform, has transformed content creation, helping everyone to create video content without cameras or microphones. To achieve this, Synthesia allows its users to create video avatars that synthesize the likeness and voice of real people. Synthesia achieves this through a series of in-house developed models based on various architectures, including