AI agents that do, not just talk.
An operating system for fleets of AI agents that execute real work on real machines — driving VS Code, git and the shell — with a person approving every action that matters, right from their phone.
Chatbots talk. The work still has to get done.
The first wave of generative AI delivered assistants that answer, suggest and summarize. Useful — but for real work, someone still has to open the editor, run the command, make the commit. Conversation doesn't turn into delivery on its own.
Assistants that stop at text
- Suggests code, but you copy, paste and tweak it by hand.
- Lives in an isolated tab, far from your real tools.
- Never touches git, the shell or your environment.
- No approval trail: either you trust it blindly, or you don't use it.
Agents that execute and deliver
- Read Work Items and follow your organization's standards.
- Drive the tools already installed on the machine (VS Code, git, shell).
- Write code + tests, commit/push and open Pull Requests.
- Every action that matters goes through human approval — with an audit trail.
From a natural-language goal to an open PR.
Three pieces keep the loop turning: a visual flow designer, a cowork agent that runs on the team's own machine, and an orchestrator that turns a goal into work routed across the fleet.
Design the flow, visually
An n8n-style flow designer: start, action, prompt, condition, parallel, join and loop nodes. The same flow contract holds, with zero drift, across web, desktop, mobile and tablet.
A cowork agent on the machine
An Electron desktop app becomes a local work agent: it drives the tools already installed and produces real deliverables. It connects outbound-only, with no open port, with a token encrypted in the system keystore — and runs headless on servers.
The fleet organizes itself
The orchestrator breaks a natural-language goal into a task graph and routes each task to the best-suited agent and machine — with automatic cost estimation, budgeting, retries and reconciliation.
Autonomy with a person in command.
ZDZCloud's method is copilot first, tested autonomy later. Every action that matters waits for a human — without ever blocking the flow. See the trust ladder →
Action Inbox on your phone
Approve, reject or pick a branch of the flow right from your phone. With auditing and timeouts, so the work never sits stuck waiting.
In and out via WhatsApp
A message triggers a flow; the result comes back as a push notification or audio on your device. Work starts and ends wherever you are.
Spending under control
Capability and budget gates before any LLM call. The fleet only spends what was cleared — and every step is logged.
Real AI at the core — not a slide.
Real multi-agent orchestration on a .NET 10 foundation, with total AI-vendor freedom: cloud or 100% local, on-premise, when the data demands it.
Semantic Kernel + Magentic
A .NET 10 backend on Microsoft Semantic Kernel, including the Magentic multi-agent pattern (Magentic-One) — real orchestration of an agent fleet.
LLM providers
Cloud or 100% local/on-premise, with no AI-vendor lock-in. You choose where the model runs — including inside your own network.
IDE/CLI integrations
Agents drive the development tools your team already uses, instead of demanding yet another isolated window.
Native MCP
Any Model Context Protocol server instantly becomes an agent tool. Connect what you already have.
Enterprise security
A desktop agent with an outbound-only connection, no open port, a token encrypted in the keystore, shell/FS sandboxing and per-organization scoping.
Multi-tenant and white-label
A multi-tenant foundation, ready for you to operate under your own brand — or resell the platform as your own product.
Not theory. A fleet of agents already builds our own products.
Pet Planner, a ZDZCloud multi-platform SaaS (web PWA + native app), is built by an AI-agent software factory — in a spec-driven pipeline with human approval between phases. And the AI economics are measured, not estimated.
What people usually ask
Is this just another chatbot?
Do I have to send my data to someone else's cloud?
How does human approval work?
Is the agent on my machine safe?
Do you actually use this, or just sell it?
Watch a goal become a Pull Request.
Book a demo and a diagnosis of your workflow. We'll show you, live, the agent fleet executing — with you approving every step from your phone.