AI Agent Orchestration

Tell it what to do.
Watch it get done.

dogud plans, runs, and verifies multi-step agent work end to end — so instructions turn into finished outcomes, not just chat replies.

4.8k+workflows run weekly
92%tasks completed unattended
<3minmedian time to first result
in plan fetch act write
TRUSTED BY TEAMS AT NORTHWINDVELOXARBOR LABSKESTRELOUTPOST
The loop

One instruction becomes a supervised pipeline.

Every run moves through the same four checkpoints, so you always know where an agent is and why.

01 · Plan

Breaks the ask into steps

dogud reads the instruction, checks what tools and data are available, and drafts an execution plan before touching anything.

02 · Act

Runs the steps

Agents execute against your real tools — APIs, files, browsers — logging every action as it happens.

03 · Verify

Checks its own work

Before marking anything done, dogud re-checks the output against the original ask and flags anything uncertain.

04 · Report

Shows you what changed

You get a plain-language summary plus a full trace, so nothing happens in a black box.

Why teams switch

Built for work that has more than one step.

live

Full execution trace

Watch each step run in real time, or come back later and replay exactly what the agent did and why.

connect

Bring your own tools

Connect existing APIs, internal systems, and data sources. Agents work with what your team already uses.

control

Approval checkpoints

Require sign-off before anything irreversible — a send, a delete, a payment — happens on your behalf.

"We stopped asking whether the agent could do the task, and started asking whether we'd checked its work. That's a different, better problem to have."

Head of Ops, mid-market logistics company

Ready when your workflow is.

Start with one workflow. Add the next once you trust the first.