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Readiness check
Five minutes. One starter system named for your clinic.
Seven dimensions, scored. One first-move question.
A read of where you are, where you should aim, and one system
to start with. You leave with a one-page diagnosis whether or not we work together.
Three quick questions to confirm we’re built for your situation. Seven scored questions across the dimensions that move the math. One first-move question that names the system where the lift is biggest.
Start the readiness check
Confirming the fit
What kind of practice do you run? Physiotherapy, chiropractic or RMT. Allied health on Jane App, Cliniko and similar. Eye care. Optometry clinic, with or without optical retail. Dental practice. General dentistry, orthodontics, hygiene. Medical aesthetics. Injectables, skin, laser. Another kind of clinic. Family practice, mental health, other. We’ll route you to a fit call. Not a clinic. Another BC service business. We’ll route you to a fit call.
Confirming the fit
Where is the clinic? British Columbia. Elsewhere in Canada. Outside Canada.
Confirming the fit
Roughly, what’s your annual revenue?
We use this to confirm the math on a KindLoops engagement works for you.
Honest answer
We don’t think we’re the right fit yet.
Strategic alignment
How clearly tied to revenue, time, or cost is your AI plan today? We don't have a plan yet — AI is a thing we keep meaning to look at. There's interest, but no specific outcome we're aiming at. We have a few outcomes in mind — revenue, hours saved, or response time. Specific targets, owners, and a measurement plan are in place.
Business value
How quantified is the value you expect AI to create? We can't put a number on it yet. There's a vague sense of upside but no math. We have a rough projection but no source for the assumptions. Conservative projection with cited assumptions and a measurement cadence.
Operating model
When AI does something, how do you handle review and rollback? We'd hand AI the wheel and hope. We'd review some of it, sometimes. We have a habit of reviewing AI output before it ships externally. Bounded jobs, human review gates, and a rollback plan per workflow.
Literacy and culture
How comfortable is the team with using AI in real work? We've barely tried it. A couple of us have played with ChatGPT. Several of us use AI weekly for real tasks. AI is part of how the team works — with a shared sense of what it should and should not touch.
Governance and ethics
How clear are your rules about AI and customer data? We haven't thought about it. We assume the tool vendors handle it. We have a few rules — what AI can see, what stays out — but they're informal. Written data-handling rules, no-training contracts, and a privacy posture you can show a customer.
Technical infrastructure
How well do your tools talk to each other? They mostly do not. Lots of copy-paste. A few integrations exist; the rest is manual. Core tools are connected; one or two important seams are still manual. Tools are integrated where it matters and we know which seams we chose to keep manual.
Data readiness
How findable, clean, and trustworthy is the data AI would need to work on? We're not sure where most of it lives. Data exists but is messy enough that we'd hesitate to feed it to anything automated. Core datasets are reasonably clean; some clean-up needed before automating. Clean, organised, and we trust it enough to act on automatically.
First move
Which of these is the biggest pain right now?
Pick the one that costs you the most time, money, or sleep this month.
Inquiries, forms, and pre-visit questions sit too long before someone replies. Patients and prospects ask basic questions out of hours, and we miss them. Calls go to voicemail outside staffed hours, and we don't always call back. Reminders, recalls and post-visit follow-ups don't go out consistently. We have past patients we could bring back but mostly don’t. Intake forms, referrals and insurance paperwork eat hours. Our booking system, phone and marketing tell us different things. We don't get many reviews, and our Google profile is out of date. None of the above is the main pain right now.
Reactivation check
Roughly how many past patients are on the list?
Reactivation math gets fragile under 500 patients, so we want to set the right expectation.
Under 500. 500 to 1,999. 2,000 or more.
Almost done
Where should we send the diagnosis?
Your result lands on screen now and copies to your inbox so you have it later.
We don’t share your address or use it to train AI models.
Your diagnosis
In the next twelve months
—
Recommended next step
A 30-minute fit call.
Your situation doesn’t map cleanly to a single system yet,
so we want to talk before recommending one.
Thirty minutes, no pressure, and a one-page diagnosis whether we work together or not.
Score: — / 28 ·
Diagnosis sent to — .
