Give your team an AI setup they can share — and you can stand behind.

Your best people have built their own AI workflows. Jetty is how you turn those into shared assets the whole team can run — with visibility, controls, and the flexibility to change models when you need to.

What you're seeing right now

One or two people on your team are getting magical results from AI. They've figured out a workflow. It's quietly saving them hours a week. Everyone else is stuck — using the same tools, getting worse output, not knowing what they're doing wrong.

You want to close that gap. And you want to do it without creating three new problems.

You don't know what AI tools your team is using — let alone what data is going into them.
The “magical” workflows live in one person's browser history. When they're out, the work stops.
AI spend is growing. You can't point to exactly what it's buying.
A new model comes out, everyone's workflows behave differently, and nobody knows why.
You're one vendor-lock-in decision away from a problem.

What Jetty is, for a team

Jetty takes the workflows your best people have already built and turns them into runbooks — short markdown documents anyone on the team can run, with the standards and checks built in.

You get a shared library of runbooks. Your team gets reliable AI workflows they can run without needing to be the person who built them. You get visibility into every run, a record of what was produced, and the flexibility to switch models without rewriting the workflows.

Read more about what a runbook is here. In short: a runbook is a skill plus a standard for “done” plus a way to check the work. You — or your team — write it once, and it runs the same way every time.

How it works

1. Turn existing workflows into runbooks.

Your best people already have the raw material. Prompts they refined. Skills they built in Claude or ChatGPT. Checklists in Notion.

Jetty converts those into runbooks — markdown documents with the task, the standards, and the self-check built in. The person who built the workflow stays the author. The rest of the team runs it.

2. Run them in a shared workspace.

Your team runs runbooks through Jetty. Every run happens in a private workspace that's cleared when the job finishes. Your data stays yours.

You see who ran what, when, and what it produced. You see cost per run, cost per workflow, cost per person. When something goes wrong, the full record is there to learn from.

3. Change the model, keep the work.

The runbook is yours. The AI is replaceable. If a better model ships, you change one setting and everything keeps working. No rewriting, no re-training your team, no quiet regressions.

Read more about why this matters in model- and agent-agnostic.

What this looks like in practice

You lead a forty-person team: marketing, sales ops, customer support, finance.

Marketing has a runbook for reviewing content against the brand voice guide. It runs on every draft before it goes to the marketing lead. Frees the lead from being the voice-compliance bottleneck.
Sales ops has a runbook for cleaning up inbound lead data — flagging duplicates, normalizing company names, matching to accounts. Runs nightly. The SDR team sees clean data in the morning.
Customer support has a runbook for classifying incoming tickets and drafting first-response templates. Runs on every new ticket. A human still reviews and sends — but the draft is already there.
Finance has a runbook for reviewing expense submissions against policy. Flags anomalies for the finance team to look at. Clears the obvious stuff automatically.

Each of these is one markdown file. Your team library is a folder of them. When you hire someone, they inherit the folder. When someone leaves, the work continues.

The three things you're probably worried about

“What about data security?”

Every runbook runs in a private workspace that's destroyed when the job finishes. Your data doesn't train the model. You control what files go in and what comes out. You have an auditable record of every run.

For teams with stricter requirements, we can run Jetty inside your cloud or on-premises. If your legal or security team needs to review anything, we have a call that covers that in detail.

“What if my team won't adopt it?”

They don't have to, all at once. The pattern that works is: start with the one person who's already bought in — the one who's built the skill, the one doing the work manually. Their runbook is the seed. Other people start using it because it saves them time. The library grows from there.

We've watched this happen. The runbook is easier to adopt than a new tool, because it's doing work the person was going to do anyway.

“What if we bet on the wrong AI vendor?”

You won't, because your runbooks aren't tied to any vendor. They're markdown files with instructions. They work with Claude today. They'll work with whatever ships next year. You keep the instructions. You swap the model.

This is the part most leaders miss when they're evaluating AI platforms: the question isn't which model to pick, it's how to stay portable when the answer changes.

Ready to see it?

Book a team walkthrough →

Bring one workflow your team runs manually today. We'll turn it into a runbook on the call.

Or, if you want to understand the shape of the thing first:

Read: What is a runbook? →