Deploy safe team apps with your AI

The AI can do it, and somebody still does it by hand

The thing your AI worked out becomes something that runs on a schedule, as a workflow, or when another system calls it. Nobody has to start it.

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The Challenge

The AI does it perfectly in a chat window, and then somebody does it by hand every Monday anyway
The pilot worked. Nine months later it is still a pilot
It only happens when the person who set it up remembers to run it
Making it run for real means asking engineering, and engineering already has a roadmap
You can show what the AI did once. You cannot point at anything it now does without you

The Runwork Solution

Put it on a schedule and it runs at the time you picked, whether or not anyone is at a machine
Turn a process with several steps into a workflow that runs step by step on the server, and retries a failed step three times on its own before it stops and tells you
Give it a web address, so another system can start it without anyone opening a chat window
Hand a task to an agent that carries it out on its own and reports back when it is done
Give the team a small tool with a screen, instead of a prompt they have to be told about

What your team gets

The Monday report nobody has to ask for

The summary somebody produced by hand every Monday morning runs on a schedule instead. It is there before the first person opens a laptop.

A process with more than one step

Pull the data, check it, write it back, tell somebody. It runs as a workflow on the server, waits at a step that has to wait, and retries a failed step three times before it stops and tells you.

Something another system can call

Your form, your CRM or a partner sends a request to a web address and the work happens. No chat window involved anywhere in it.

A tool your colleagues can open

Some work needs a screen, not a prompt. The AI builds a small internal tool with a page people can use, and the team uses it without being taught a prompt.

A task handed over completely

An agent takes the job, works through it on its own and comes back when it is finished. Nobody sits and watches the run.

The pilot that became the process

The thing that proved AI could do it stops being a demonstration. It is now how the work gets done, and it runs whether or not the person who set it up is thinking about it.

A Day in the Life

Monday, 7:40 AM. Before anyone starts. The weekend summary is already written. It runs as scheduled work on the server rather than as a thing somebody does first thing, so the day starts with reading it instead of making it.

9:15 AM. A form gets filled in somewhere. A customer submits a request on your site. That hits a web address in your workspace, which starts the intake work: the record is created, the right person is told, the reply goes out. Nobody opened an AI tool to make any of that happen.

11:00 AM. A step has to wait. The reconciliation workflow gets to the step that needs the bank file, and the bank file is not there yet. It waits, and continues from that step when it arrives, rather than starting the whole thing again from the top.

2:00 PM. Somebody uses a tool, not a prompt. Your ops colleague opens the internal tool that was built for this exact job and does the thing. They were never taught a prompt, because there is no prompt to teach.

4:30 PM. A job you handed over entirely. An agent has been working through the vendor list on its own. It comes back with what it found. You did not sit and watch it, and you did not have to be the one who remembered to start it.

6:00 PM. You leave, and the work does not. Tomorrow's scheduled jobs are set, the workflow is waiting for its file, and the web address still answers. None of that depends on your machine being open.

Frequently Asked Questions

How do I turn something my AI does into something that runs by itself?

You decide what starts it. A schedule starts it at a time you choose. A public endpoint lets another system start it. A workflow runs several steps in order. In each case the work moves off the chat window and onto the server, and that is the whole difference between a thing your AI can do and a thing your company does.

What is the difference between a schedule and a workflow?

A schedule is about when: the same job runs again at a time you set, and nobody has to remember it. A workflow is about steps: several pieces of work run in order, each one waiting for the one before it, and a step that fails is retried three times on its own before the run stops and tells you. Plenty of real work uses both, with a schedule starting a workflow.

Does this still run when I close my laptop?

Yes. Schedules, workflows and endpoints run on the server, not on anybody's machine, so shutting a laptop does not stop them. The skills and instructions the work depends on are saved in the workspace as well, so nothing it needs is sitting on your laptop either.

Do I need engineering to put this live?

No, and that is usually the whole reason a pilot stops at the pilot. The person who worked the thing out with their AI is the person who puts it on a schedule or turns it into a workflow. Nothing waits for a slot on somebody else's roadmap.

Can other systems trigger this work?

Yes. A public endpoint gives the work a web address, so your website, your CRM, a partner or any tool that can send a request is able to start it. The work does not care whether a person or a system asked for it.

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