Launched this week
ZooWork lets you build, deploy, and deliver AI agents to teams or clients — experts start in the Builder UI, developers ship with the Managed Agent API. Turn your expertise into AI solutions built for real business operations.
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the domain-expert-builds-it-in-the-UI model is the interesting bet here. at Dial we've seen non-technical team members want to tweak a live call flow and the thing we worry about isn't whether they can, it's whether a change they make on a Tuesday afternoon quietly breaks something for a client on Wednesday. is there any review or staging step before an expert's agent update goes live for a client, or does it publish straight through once they're happy with it in the Builder?
@galdayan You can test changes in a new chat session inside the Builder before they go live. An update is only published when you manually click Publish. Try revising one instruction, testing it in a fresh session, then using Publish when you're happy with the result.
@david_srp good to know, the test-then-manually-publish split is exactly the right default for this. that said, the failure mode I'd still worry about is the expert testing the happy path in their fresh session and never trying the edge case that actually breaks - is there anything like a diff view or a changelog so a second person can sanity check what changed before it goes live, or is it fully trust-the-editor?
Congrats on the launch! 🎉 The hardest part of building my own agents has been data — self-built scrapers are a maintenance sink, and paid APIs get pricey and aren't always trustworthy. How does ZooWork handle data access for an agent — does it pull data itself through built-in tools, or are there connectors / data partners in the mix?
An HR consultant could package a workshop intake questionnaire into an agent and share it with clients before the session.
@genedai Exactly—and the consultant’s experience is what makes that intake valuable: knowing which questions to ask, what to follow up on, and what needs a deeper conversation. That’s the expertise we want to help turn into a usable agent. Try it with your own questionnaire—we’d love your feedback! DM me to get a coupon code if you want to take a try.
An operations advisor could package a process diagnostic checklist into an agent and let clients run an initial assessment before a workshop.
@lynzhong_ You're right, and I've tried this exact approach myself. I built an enterprise AI adoption diagnostic this way in about half an hour: https://zoowork.ai/insights?lang=en It's a few business questions with no sign-up, and you get a short report at the end. Want to give it a try?
@priyankamandal Thanks, Priyanka! I'd start with a workflow you know well, write your own steps into the Builder, and share the Agent with one teammate. Their feedback is a good way to see whether your expertise is coming through in the result.
"Works beautifully on my laptop" is the most honest line in AI right now. I have at least three agents in that exact state. 1–2 second cold starts and paying nothing while idle is the part that got me. Congrats Ning and team!
@chang_chen_growth Thanks, Chang! Pick one of those three and deploy it through our Managed Agent API, then have a teammate run a task it already handles well. We take care of the runtime, so you can focus on whether it works for them too.