# Google Expands Gemini Into an Agent Platform for Building and Running Business AI > Source: > Published: 2026-08-26 18:45:30+00:00 Google Cloud has introduced **Gemini Enterprise Agent Platform**, a developer platform intended to bring AI agent creation, deployment, runtime operations and governance into one product surface. The April 23, 2026 announcement marks a broader shift in how Google is positioning Gemini for business use: not simply as a model that answers prompts, but as part of a stack for building long-running agents that can carry out defined work across company systems. According to [Google Cloud's announcement of Gemini Enterprise Agent Platform](https://cloud.google.com/blog/products/ai-machine-learning/introducing-gemini-enterprise-agent-platform?hl=en), the Agent Platform evolves the services previously associated with Vertex AI into a unified platform. It combines model access, agent development tools, runtime infrastructure and operational controls. Google is also extending the broader Gemini ecosystem through Gemini API previews, Google AI Studio, Antigravity, Android development support, the Gemini app on macOS, Gboard features on Android, and planned Gemini Enterprise for Customer Experience capabilities. The important distinction is that Google is describing a platform for agents that can persist over time, retain relevant context and interact with tools, rather than a collection of isolated chatbot features. For companies exploring automation, that could make it easier to move from one-off AI experiments toward applications designed around repeatable workflows. It does not, however, remove the need to define reliable processes, permissions and human oversight before deploying an agent in a customer or operational workflow. Google describes the Agent Platform as the runtime and governance layer for production-scale AI agents. It is built around three connected areas: creating agents, running them with context and tools, and observing or controlling their behavior once deployed. **Agent Studio** provides a low-code interface for building agents. Developers can also use the upgraded **Agent Development Kit (ADK)**, while the reworked **Agent Runtime** is intended for long-running, stateful agents. Google says **Memory Bank** provides persistent context, a key capability when an agent must retain relevant information across a multi-step task instead of treating each interaction as entirely new. The platform also includes tools aimed at managing agents in operational settings. These include Agent Identity, Agent Registry, Agent Gateway, Agent Simulation, Agent Evaluation, Agent Observability and Agent Optimizer. Google frames these as part of the security, identity, governance and evaluation foundation needed to deploy agents at scale. | Platform area | Google capability | Practical purpose | |---|---|---| | Agent creation | Agent Studio and Agent Development Kit | Build agents through a low-code interface or developer tooling. | | Agent execution | Agent Runtime and Memory Bank | Support long-running, stateful agents with persistent context. | | Operational controls | Agent Identity, Registry, Gateway, Simulation and Evaluation | Manage access, test agents and assess their behavior. | | Model access | Model Garden | Use [Gemini models](https://scalevise.com/resources/gemini/) and supported third-party models from one catalog. | Model Garden is central to the platform's scope. Google identifies Gemini models including Gemini 3.1 Pro, Gemini 3.1 Flash Image, Lyria 3 and Gemma 4, while also supporting third-party options such as Claude Opus, Sonnet and Haiku. That multi-model approach may matter when a team needs to test models against a particular task rather than committing an entire application to one model family. Google also positions the Gemini Enterprise app as an employee-facing front end for delivering agents inside an organization. In other words, an organization can build or configure agents in the platform and provide a controlled place for staff to use them. The announcement emphasizes alignment with security and IT operations, although the specific setup required will vary by use case and environment. The Agent Platform is not an isolated release. Google has disclosed related updates that connect experimentation, application development and deployment across its Gemini products. The [ Gemini API public preview](https://scalevise.com/resources/google-gemini-3-7-flash-ga-ai-mode-api-pricing/) through Google AI Studio includes Gemini 2.5 Pro Preview, with billing-enabled previews and, in some cases, an integration path into Vertex AI. This gives developers a route to test Gemini capabilities through the API before deciding how a production implementation should be run. Antigravity 2.0 adds another layer. Google describes it as including a standalone desktop application, command-line interface and software development kit for managing and deploying agents across Google AI Studio, Android and Firebase. Google has also signaled Managed Agents in the Gemini API and an integration path into Gemini Enterprise Agent Platform. For teams building customer-facing or mobile experiences, Google has announced [native Android support in Google AI Studio](https://scalevise.com/resources/gemini-chrome-android-rollout-features/) and the Interactions API for Gemini. Workspace integration and export paths to Antigravity further connect these tools. At the user interface level, Google has also pointed to a Gemini app for macOS and Gemini-related features in Gboard on Android devices. Google's planned **Gemini Enterprise for CX** extends the strategy toward customer experience. The company has signposted CX Agent Studio, Agent Assist, CX Insights and Commerce agents. These products indicate where Google sees practical demand: agents that assist employees, support customer interactions and contribute to commerce-oriented processes. The available announcements do not fully specify timing, regions or exact availability across every component. For a business evaluating this ecosystem, the sensible starting point is not a broad promise of autonomous AI. Start with a process that has clear inputs, a defined output and a meaningful manual burden. Candidate workflows could include drafting responses for staff review, organizing information from recurring requests or assisting an internal team with knowledge retrieval. A useful early evaluation should establish: Pricing is not yet clear across all products and tiers, particularly for smaller organizations. Regional rollout timing and the precise availability of cross-product integrations also remain open questions. Those gaps make a narrow pilot more practical than designing a large program around features that may not yet be available in a particular location or plan. For businesses, the opportunity is to connect model access and agent tooling to work that already exists, rather than treating generative AI as a standalone interface. **Scalevise can help map a high-value workflow, select an appropriate implementation path and design practical safeguards before resources are committed.** If your team wants to turn a recurring manual process into a dependable AI-assisted workflow, [discuss an AI automation project with Scalevise](https://scalevise.com/contact) and request a consultation. **What is Gemini Enterprise Agent Platform?** Gemini Enterprise Agent Platform is Google Cloud's unified platform for building, deploying, operating and governing AI agents. Google presents it as the evolution of Vertex AI services into a broader agent-focused platform. **What tools are included in the Agent Platform?** Google highlights Agent Studio, the Agent Development Kit, Agent Runtime, Memory Bank, Model Garden, and operational tools such as Agent Identity, Agent Registry, Agent Gateway, Agent Simulation, Agent Evaluation, Agent Observability and Agent Optimizer. **Can developers access Gemini through an API?** Yes. Google has disclosed a Gemini API public preview through Google AI Studio that includes Gemini 2.5 Pro Preview. The research also notes billing-enabled previews and integration into Vertex AI in some cases. **Is pricing available for Gemini Enterprise Agent Platform?** The supplied announcements do not provide complete pricing details or specific tiers for smaller organizations. Businesses should confirm current pricing and regional availability with Google before planning a deployment. Gemini Enterprise Agent Platform gives Google a more coherent way to connect model access, agent development, runtime infrastructure and operational controls. Its value for businesses will depend less on the breadth of the stack than on whether teams apply it to clearly defined workflows, test it carefully and confirm availability and cost before scaling.