Runwork for SaaS Teams

Your team does real AI work all day. None of it reaches the next person.

Support has a way of triaging with AI. Success has a renewal-risk prompt that works. Neither knows about the other. On Runwork it all lands in one place, every teammate's AI can use it, and it carries on with nobody watching.

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The Challenge

Support worked out a triage method with AI. Success never hears about it.
The internal tool someone made lives on the laptop of whoever made it
Engineers get pulled off the product to rebuild the same admin screen
Nobody can find the link to the thing that already exists
Metrics come from three systems and one person's spreadsheet

The Runwork Solution

One place where support, success and ops AI work all lands
What one team teaches their AI, every other team's AI has the next morning
The tools your team's AI makes get a real deployment, backups and permissions
Customer context in one view that every teammate's AI can read
Metrics pulled from Stripe and your product data on a schedule, not the night before the meeting

What your team gets

One customer view everyone's AI can read

Subscription, usage, support history and billing in one place, so support stops guessing and success stops asking.

The triage method, shared

What your best support lead taught their AI is what every teammate's AI does by Monday, including the two people who joined last week.

Onboarding that chases people for you

Each new account's progress tracked, nudges sent on their own, and you step in only where a human actually helps.

Revenue numbers without spreadsheet assembly

MRR, churn and forecast pulled from Stripe and your product data on a schedule. One link, and everyone sees the same numbers.

Internal tools that outlive whoever made them

Whatever your agent codes gets a real deployment, live previews, backups and permissions, in a place the team can find. Not a preview link buried in someone's chat.

Support patterns you spot in hours

Tickets grouped as they arrive, so engineering gets Zapier trigger failing on X config instead of something is broken.

A Day in the Life

8:00 AM: Customer escalation. An account needs attention. You open the customer view: subscription, usage, support history, billing, one screen. They hit their API limit yesterday. You upgrade them there and the Stripe integration handles the billing change. Nobody on the call had to ask anybody else for context.

10:00 AM: Onboarding check. Three new customers this week. One finished setup, one is stuck on the API step, one has not started. The stuck one already got a nudge, so you spend your time on the one who has not started. This runs on a schedule, so it happened before you opened your laptop.

1:00 PM: Metrics review. MRR up 8%, churn down 0.5%. The data comes from Stripe, your product database and your support tools, assembled overnight rather than by someone at 11 PM the night before. You share one link and the meeting is about the numbers instead of about whose numbers are right.

3:00 PM: The tool support asked for. Support wants a screen that shows failed webhooks by account. Their lead describes it to her own AI, it vibe-codes the thing in an afternoon, and it lands in your team cloud with a live preview, backups, permissions and a real address. Engineering did not get a ticket, and in six months it will still be there, because it is not a preview link in somebody's chat history.

4:30 PM: Support patterns. A spike in integration-not-working tickets, all from customers using the new Zapier trigger. You hand engineering the pattern, not the complaint: Zapier trigger failing for accounts with X configuration. The grouping rule came from a teammate who worked it out months ago and never had to explain it twice.

5:30 PM: Who else has it. On the team dashboard you can see which teams are using the triage skill and the renewal-risk one, and which are not. Support is all in. Two people in success have not touched them. That is a short conversation tomorrow, and it is the reason this compounds instead of staying with one clever person.

Frequently Asked Questions

Our support and success teams already use AI. What changes?

What they work out stops staying with them. The triage method one person perfected, the renewal-risk prompt someone else swears by, they land in one shared cloud and every teammate's AI can use them. Nobody switches tools, and nobody pastes a prompt into Slack again.

Where do the internal tools our team makes actually live?

In your team cloud, with a real address. Your own AI agent (Claude, ChatGPT, Cursor) does the coding, and Runwork is the environment it lands in: live previews while it is being made, code and data backups, permissions, monitoring, and a place your team can find it later. That is the difference between a tool and a link somebody lost.

Can we connect it to Stripe, our product database and our support tools?

Yes. Stripe for billing, your product database for usage, Intercom or Zendesk for support, and anything else with an API. Your data stays where it is, and your team's AI can reach all of it in one view.

How does workspace isolation work for multi-tenant data?

Each workspace has its own data, users and permissions, so teams or customers do not see each other. The same tool can run in several workspaces, which is what you want for customer-facing dashboards where everyone should see only their own numbers.

Can non-engineers keep these tools working?

Yes. They talk to their own AI the way they already do: add a field to the admin panel, change how churn is calculated. The change deploys, gets versioned and backed up, and everyone is on the new version. No ticket, no sprint, and nothing lost if that person leaves.

Can we see who on the team is actually working this way?

Yes, and for SaaS teams this is usually the surprise. The team dashboard shows which skills and tools people use and who has not started. You find out that support is compounding and success is stuck, while you can still fix it.

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