From first pilot to a governed digital workforce.
Gemini Enterprise puts agents to work across your organization. The Gemini Enterprise Agent Platform builds, scales, and governs them. Dito is the Google-dedicated partner that guides both: proving value on a real process first, securing agents like the workers they are, and running the governance when you would rather not build that function yourself.
Google-dedicated since 2007
The engagement, in four layers
Gemini Enterprise
The agentic platform for your workforce: agents, Inbox, Canvas, and Projects in one workspace.
Right-fit architecture
The agents, models, and connectors your processes actually need. Nothing speculative.
Security & Governance
Every agent gets an identity, a boundary, and an audit trail before it gets autonomy.
Managed AgentOps
Dito operates the governance layer as a service when you would rather not staff it.
Tokens processed monthly across Google AI surfaces
Monthly active users of the Gemini app
Google Cloud customers each processing 1T+ tokens a year
Developers building with Google models each month
Platform figures reported by Google, I/O 2026
Chatbots answered questions. Agents do work. That changes what you are accountable for.
A chatbot answers when asked. A workflow follows the script it was given. An agent pursues an outcome: it plans, calls tools, acts across your systems, and decides what to do next. That third category is where the productivity is. It is also where the accountability lives, and it puts three decisions in front of most leadership teams before a specialist is in the room:
The platform is moving faster than your review cycle.
In April 2026, Vertex AI evolved into the Gemini Enterprise Agent Platform. Weeks later, I/O brought Antigravity 2.0, Managed Agents in the Gemini API, and Gemini 3.5 Flash. Waiting for the picture to settle is not a strategy. The picture does not settle.
Everyone in your company can now build an agent.
Agent Designer lets any employee create agents in natural language. That is the point of an agentic workplace, and it is also how you get shadow AI at machine speed: agents without owners, identities, or boundaries. The answer is not to slow your people down. It is to govern what they build.
The governance question arrives with the first production agent.
Boards, auditors, and regulators will ask the same three things: who authorized this agent, what data did it touch, and why did it act? The controls exist on the platform. Someone has to design them, operate them, and answer for them.
"An agent is not a feature you switch on. It is a digital worker you onboard, permission, supervise, and audit."
The operating principle behind every Dito agent deployment
The distinction that runs through this page: chatbots respond, workflows execute, agents decide. Each step up multiplies the value and the need for governance. Dito's practice is built for the third step.
One agentic stack, from silicon to your workforce.
Google is the one provider that owns the entire stack: custom TPUs and infrastructure, frontier models, the platform that runs agents, and the workspace where employees put them to work. Dito helps you compose the right pieces for your organization, then keeps the composition secure and efficient as adoption grows.
The workplace
Gemini Enterprise
The agentic platform where your workforce creates, runs, and supervises agents. Agent Designer builds agents from natural language, no code required. The Inbox manages long-running agents and routes approvals to humans before consequential actions. Canvas co-creates documents and presentations.
8M+ paid seats across 2,800+ companies
The factory
Gemini Enterprise Agent Platform
The evolution of Vertex AI: one environment to build, scale, govern, and optimize agents across their whole lifecycle. Build with the Agent Development Kit or any open-source framework. Deploy on Agent Engine's managed runtime. Every agent carries a unique Google Cloud identity.
Four pillars: build, scale, govern, optimize
The storefront
Gemini Enterprise for CX
The agentic suite for retail, restaurant, and service brands. A Shopping agent reasons across catalogs and applies promotions through checkout, while human-voice support agents handle service end to end. AI Commerce Search personalizes discovery seamlessly.
Live today at major enterprise brands
The foundation
The full Google stack
Gemini 3.1 Pro for deep reasoning, Gemini 3.5 Flash for high-frequency agentic work, Veo for generative video, and Model Garden for third-party models, all running inside your security boundary on Google's own TPUs. Antigravity 2.0 connects your engineering teams to the same Agent Platform project.
MCP + A2A open protocols for cross-vendor interoperability
Four stages. One discipline, from first agent to standing workforce.
The platform is documented. What is not documented is how your organization moves through it: which process earns the first agent, what security has to be true before autonomy, and who answers for the estate once it is running. This is the path we architect.
Prove value on one real process, in weeks, with a human approving every consequential action
We start where agents earn belief: a bounded process with measurable friction and a success bar defined up front. The first agent is built in Gemini Enterprise or with the Agent Development Kit, grounded in your data, and evaluated against your quality bar before anyone depends on it. Supervised before autonomous: every consequential action routes through the Inbox for human approval until the evidence says otherwise.
Where Dito earns its keep: use-case selection and sequencing, success criteria your CFO will accept, and a pilot designed to produce evidence rather than a demo.
No-code, natural language
Federated access
Human-in-the-loop by default
Managed AgentOps: your AI governance function, delivered as a service
Some organizations will build an internal AgentOps team. Most should not have to before the value is proven. Dito operates the security, governance, and operations layer of your agentic estate: agent identities and permissions, evaluation regimes, runtime monitoring, and the reporting your leadership and auditors expect.
It is the same operating discipline behind our Managed Google SecOps practice, applied to a new class of worker. Two managed practices, one boutique firm: your SOC watches your infrastructure, and your AgentOps function watches your agents.
Model 01
Fully Managed
Dito operates AI governance end to end: identities, gates, monitoring, and a standing report to your leadership. You own the outcomes; we run the function.
Model 02
Co-Managed
Dito specialists embed inside your team: staff augmentation with a practice behind it. Your people keep control; ours bring the depth and the bench.
Model 03
Operate and Transfer
We stand up the AgentOps function, run it to a steady state, and train your team to take it over on a defined timeline. Capability building, not dependency.
A boutique partner with one focus, since 2007
Google-dedicated, not Google-adjacent
One hundred percent of our practice is built on Google Cloud. Depth over breadth: when the platform moves, we already know, because it is the only platform we serve.
Security DNA in the AI practice
The firm that operates a managed SOC on Google SecOps designs your agent governance. We treat agents with the discipline that implies: least privilege, evidence, and review.
A streamlined conduit to Google
One relationship for licensing, program guidance, and roadmap signal. When Google ships something your plan should know about, you hear it from a named expert.
Boutique agility, enterprise execution
You work with people who know your architecture, not a rotating cast from a global bench. White-glove responsiveness with the technical depth to run production.
The questions technology and security leaders ask us first
See what a digital workforce would do in your business.
The AI & Agentic Workplace Briefing: a 30-minute working session with a Dito architect. Your processes, the candidate agents, and the governance path. No pitch deck.
- Which of your processes are agent-ready, and which one earns the pilot.
- What security and governance have to be true before an agent gets autonomy.
- Whether Managed AgentOps or an internal function fits your organization.
