Google has also upgraded the workspace and data infrastructure. <\/li>\n<\/ul>\n\nAs companies use more agents in their workflow, managing them securely and efficiently becomes a primary challenge. Google has just created a potential solution, wrapped in the same accessible interface that many teams are familiar with. <\/p>\n
On Wednesday at the company’s annual enterprise conference, Google Cloud Next, Google released its new Gemini enterprise agent platform for developers. Developed from Vertex AI, the Agent Platform “brings together Vertex AI’s model selection, model building, and tuning services that customers love, along with new features for agent integration, security, DevOps, orchestration, and more,” CEO Thomas Kurian said in the announcement. <\/p>\n
Plus: This powerful Gemini setting made my AI results more personalized and accurate<\/strong><\/p>\nThe platform refreshes the current Gemini enterprise experience and offers over 200 models, including Gemini 3.1 Pro, Nano Banana 2, Gemma Open models, and Anthropic’s competing models, such as its recently released Opus 4.7. Since the Agent Platform is built on Vertex, Google noted that those services will now flow exclusively through the Agent Platform. <\/p>\n
All-in-One Agent Building <\/h2>\n
In the platform, according to Google, developers can design an agent’s life cycle from start to finish, from creating the agents themselves to scaling and controlling them. MCP support and an advanced agent development kit help developers maximize reasoning capabilities by structuring agents into sub-networks. Google said that tiered approach should prepare agents to handle complex tasks, adding that faster runtimes and other features like memory banks help agents delegate to each other more efficiently and work with more context for longer periods of time. <\/p>\n
“Gemini Enterprise Now is an end-to-end system for the agentic age, built for agents who can execute complex, multi-step work processes,” Google said in the announcement. <\/p>\n
Also: Long-term AI use can be dangerous to your health and work: 4 ways to stay safe<\/strong><\/p>\nThe company also emphasized that it has built security into the new platform through tools like Agent Identity, which assigns a cryptographic ID to each agent. However, if you don’t want to take any risks, you can use Google’s new agent simulation tool to “stress-test your agents against real-world scenarios before shipping,” the company said. <\/p>\n
Once developers complete building and testing, they can publish agents from the platform to Gemini Enterprise apps, where employees can run those agents or create their own with no-code or low-code options like Google’s Agent Studio and Agent Designer. <\/p>\n
A Google employee demonstrated how users can deploy multiple agents together in enterprise apps to tackle an inventory or marketing challenge, as if they were a team of workers. In the demo, each individual agent handled a specific element of a multi-phase project for a furniture company, using the organization’s workbench content to pull relevant data and strategy points. <\/p>\n
Security <\/h2>\n
Running multiple autonomous agents can create numerous privacy and security risks for any organization, especially when non-developer employees use them. Google emphasized that its revamped Gemini Enterprise addresses this by simplifying guardrails and permissions before users can access agents. The company said it “provides the same level of monitoring and auditing found in essential business applications such as payroll or quarterly financial reporting.”<\/p>\n
Also: I tested ChatGPT Plus vs Gemini Pro to see which is better \u2013 and whether it’s worth the switch<\/strong><\/p>\nGemini sits on top of the enterprise app agent platform, which Google said standardizes administration and security. <\/p>\n
“We provide a single control plane for administration across the agent platform, so every employee can access and share agents with full IT visibility,” the company said. \u201cBoth no-code and pro-code agents are managed through a consistent model for identity, security, and auditing.\u201d <\/p>\n
Other announcements <\/h2>\n
Google also announced the Agentic Data Cloud, a new data architecture aimed at helping AI agents scale at scale. Many new features let developers quickly query data without taking it out of AWS or Azure, leverage new data science tools across multiple surfaces, and enrich files with metadata to give agents more meaningful context, among other capabilities. <\/p>\n
At the workspace level, Google launched Workspace Intelligence, which “uses Gemini logic to understand complex semantic relationships within your workspace apps (like Docs, Slides, or Gmail) content, your active projects, your collaborators, and your organization’s domain knowledge,” the company wrote. <\/p>\n
Also: Scaling Agentic AI Demands a Strong Data Foundation \u2013 4 Steps to Take First<\/strong><\/p>\nAlthough it may seem like Gemini is already doing this, Google has designed Workspace Intelligence as an additional tool that Gemini will take advantage of when automating tasks like slide generation and project preparation. Google noted some upgrades in the new feature, including proprietary infographics in Docs and enhanced personalization to suit the user’s style. <\/p>\n
Google said, “Workspace Intelligence retrieves your relevant emails, chats, files, and information from across the web to transform your ideas into professionally formatted drafts that mimic your exact voice, brand, style, and company templates.” <\/p>\n<\/div>\n