Every gym business we've worked with has a different definition of "broken". AI agents only earns its keep when it solves the specific definition you'd give it on a bad day - which is why our first call is mostly listening.
For gyms who want results in weeks, not a year-long transformation programme.
Our goal is to give gyms a three-day weekend, so people can spend more time with their families and the people they love :)
What AI agents actually does
Autonomous AI agents that don't just answer - they get things done. They check inventory, draft proposals, file paperwork, and chase quotes while your team focuses on the human work.
- 01 Goal-driven agents that complete multi-step tasks
- 02 Connect to your tools - Xero, HubSpot, Gmail, Slack, your CRM
- 03 Human-in-the-loop checkpoints for anything risky
- 04 Full audit log of every action the agent takes
Built on: Claude Agent SDK OpenAI Agents LangGraph n8n MCP
Without Kiwi Dynamics
With Kiwi Dynamics
What you actually get
Every engagement is scoped and quoted up front. This is what is in the box.
- A working pilot, in productionNot a prototype on someone's laptop. The first slice of AI agents runs against real work within weeks.
- Your data stays yoursIt runs on your accounts and your tools. If we part ways you keep the system and everything in it.
- The workflow mapped before codeWe write down what good looks like for gyms first, so nobody is guessing at handover.
- Support after it landsThe people who built it stay reachable when the business changes shape around it.
How AI agents compares
The two things most businesses do instead, and where each one runs out.
| Hiring for it | An off-the-shelf tool | Kiwi Dynamics | |
|---|---|---|---|
| Fit to how you work | Fits perfectly, costs a salary | You bend your process to suit the tool | Built around the workflow you already run |
| Time to something useful | Immediate, and permanent | Quick to switch on, slow to make fit | A working slice in weeks, then hardened |
| Who owns the data | You do | The vendor, on the vendor's terms | You do, in your own accounts |
| When it breaks | That person sorts it, if they are in | A support queue and a ticket number | The people who built it |
| What it costs | A salary, every year, forever | Per seat, forever, used or not | Scoped and quoted up front |
The shape of every gym brief we've seen.
- Gyms and studios live or die on membership retention, and most churn happens quietly, weeks before someone cancels.
- Lead follow-up, trial conversion, and renewal reminders are the levers that decide a gym's membership numbers.
How we build AI agents for gyms.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for a gym business, so value lands before the build is finished. AI agents that do work.
Talk to usHow the work runs
- Find the one workflowWe look for the job costing gyms the most hours or the most leads, and deliberately ignore the rest for now.
- Ship a working sliceA narrow version goes into production in weeks, against real work, so the value shows up before the build is finished.
- Prove it, then widenWe measure it against what the work cost before. If it does not pay for itself, we say so rather than scaling it.
- Harden and hand overLogging, fallbacks and a real handover, so it keeps running when we are not in the room.
The outcome for gyms
The shape of the result for gyms: Replaces 15+ hours of weekly back-office work per agent deployed. Built on Claude Agent SDK, hardened with the rest of the stack as it scales.
Not your typical AI agency.
Honest about what AI can and cannot do
Ships the one workflow that pays for itself
Hours given back, never the size of the invoice
*Every engagement is scoped and quoted up front. Results vary by workflow and business.
FAQ
What's the realistic timeline for AI agents with a gym?
Most gyms have their first usable slice in week 5 or 6. We'd rather ship narrow and real than broad and aspirational - your team gets to use the thing well before the engagement is "done".
Is AI agents worth it for a smaller gym?
Often, yes - and counterintuitively the ROI is sometimes faster than for the big end of town because there's less integration overhead. We'll tell you honestly on the scoping call if it isn't.
Do you have proof this works for gyms?
Direct case study: Replaces 15+ hours of weekly back-office work per agent deployed. Happy to walk you through full numbers on a call.
What happens if we want to swap a vendor out later?
AI agents is built behind a small adapter layer specifically so swapping a model provider or a data source is a one-day job, not a re-architecture. Claude Agent SDK, OpenAI Agents, LangGraph, n8n, MCP are our defaults, but the build is intentionally portable.
Twenty minutes, your call.
You describe what's broken. We'll tell you what we'd actually do about it.
Talk to us about this
Tell us what you're trying to do and we'll reply with how we'd build it - no obligation.