AI Integration
AI that gives you the hours back.
Most clinics do not need more software. They need the hours back. We start by finding where your team's time really goes, fix the workflow around it, and only then put AI to work on the jobs it genuinely does well.
Built with a modern, owned stack
- Next.js
- TypeScript
- React
- Expo
- Tailwind CSS
- Supabase
- Neon
- PostgreSQL
- Medusa
- Stripe
- Resend
- FastAPI
- Cloudinary
- Node.js
- Vercel
- Next.js
- TypeScript
- React
- Expo
- Tailwind CSS
- Supabase
- Neon
- PostgreSQL
- Medusa
- Stripe
- Resend
- FastAPI
- Cloudinary
- Node.js
- Vercel
AI will not fix a broken process. So we fix the process first.
What it is
Built for clinics.
AI integration starts with a conversation, not a chatbot. We sit with your team, map how a normal day actually runs, and measure where the hours go: retyping results, answering the same enquiries, writing up notes, chasing paperwork. Then we decide what to fix, what to automate, and what to leave alone.
Often the biggest win is a better workflow with no AI at all. Where AI does earn its place, we connect it to the tools you already use, keep a clinician or a member of staff checking anything that matters, and handle patient data carefully under UK GDPR. You get the hours back without handing over the judgement.
Capabilities
What you get.
Time audit
We map a real day in your clinic and measure where the hours go, so we fix the biggest drains first, not the shiniest.
Workflow fixed first
Steps removed, forms simplified, and handovers cleaned up before anything is automated.
AI where it earns it
Drafting replies, summarising documents, pulling data out of PDFs, and sorting enquiries, wired into the tools you use.
A human in the loop
Anything clinical or patient facing is checked by your team before it goes out. AI drafts, people decide.
Patient data protected
The minimum data sent, providers vetted, and settings chosen so your data is not used to train their models.
Measured afterwards
We compare the hours before and after, so you know exactly what the change is worth.
Process
Five steps. Nothing hidden.
The same path on every build, from the first call to the first real number. Scroll to follow it.
Consult
We learn your clinic, your team, and what is wearing them down. Plain questions, honest answers.
Discover
We map a real day and measure where the time goes, from the front desk to the clinicians.
Fix the workflow
We cut the steps that should not exist and simplify the rest, before anything is automated.
Integrate AI
AI goes in where it saves real hours, connected to your tools, with your team checking what matters.
Measure
We compare the hours before and after, then keep improving. Time saved is the number we report.
Is this you?
This is for you if.
Your team spends hours on admin that feels like it should take minutes.
Clinicians are writing up, retyping, or summarising instead of seeing patients.
Reception answers the same questions by phone and email all day.
You are curious about AI but will not put patient data at risk to try it.
The next step
Ready to get the hours back?
Tell us about your clinic and what you want more of, or less of. We will tell you, plainly, what we would build and what it should bring back. No pressure, no jargon.
Common questions.
Not always, and we will tell you. The discovery stage often shows that a cleaner workflow saves more time than any AI tool. We only add AI where it clearly earns its place.
Drafting replies to common enquiries, summarising referral letters and documents, pulling results out of lab PDFs, sorting and routing enquiries, and preparing notes for a clinician to check. Clinical decisions stay with your clinicians.
It can be, with care. We send the minimum data needed, choose providers and settings where your data is not used to train their models, and work with your data protection lead on the details. Some jobs are best done without patient data leaving your systems at all, and we will say so.
That is not the aim. The aim is to take the repetitive work off your team so they spend more time with patients. AI drafts, people decide.
We record how long the work takes before we change anything, then measure again afterwards. You see the hours saved in plain numbers.