A Solo Vet Uses Claude-Built Tools to Catch Unbilled Work and Missed Follow-Ups
After a software switch left 19 years of records in an unsupported system, a solo vet built tools with Claude that compare each visit's notes with the invoice to catch work nobody charged for, and flag advice that was never followed up.
Who this is about: Solo veterinary practice (FutureProof.vet)
What it takes
- Cost
- PaidPay-as-you-go Claude API usage, plus a small server at the clinic.
- Setup time
- A few weeksOur estimate from the source, for one business.
- Skill needed
- Developer skillsYou build or run your own code, even if AI writes it.
Explain it simply
The vet asked Claude to help build small tools that read old and new patient records. Before each appointment the system builds a checklist for that pet, and it also looks for work that was done but not billed and follow-ups that were missed. He still makes the clinical decisions; the software just spots gaps in the paperwork.
What was done
When the clinic moved from VIA to Shepherd, the old records stayed in a database nobody supports anymore, so the vet asked Claude to help read them; the first version took about half a day. VetNexus grew from there.
Every pet on the day's schedule gets a checklist that ticks itself off from the record, Claude compares notes to the invoice, and a chart summary reads the pet's whole history the way a colleague would brief you, including a section on advice repeated but not yet followed. A second tool, Hearth Consult, acts as a case "second opinion" using free consensus guidelines and the clinic's own 217-drug formulary.
How it went
The note-versus-invoice check catches things like two extracted teeth that nobody charged for before the client leaves, and has paid for itself a few times. On its first real run, the chart summary found an ultrasound referral from months earlier that never happened. It's now the first thing the vet opens every morning.
- Limits: these are one vet's own accounts with no measured time or revenue figures. Hearth Consult was designed around AI's weak arithmetic: doses come from the clinic's formulary, plain code re-checks the math, a dose is struck through if the words and numbers disagree, and cats get hard stops on drugs that harm them.
- The owner's name and phone are stripped before anything goes to the AI, the tool runs only on a local clinic server, and the vet still reads every answer.
Prompt
Morning check: "For each appointment today, compare the medical notes with
the invoice. List any procedure, test or medication in the notes that has no
matching invoice line."
Chart summary: "Read this patient's full history and write what a good
colleague would tell me before I walk in. Include a section: 'Advice
repeated but not yet followed' (referrals, tests, diet changes)."
Guardrails from the source: doses come from your own formulary and are
re-checked by code, not by the model; strip owner names and phone numbers
before sending; keep emergency tools (CPR timer, fluid math) free of AI.Our prompts; the journal doesn't publish its own. The guardrails are from the source.
Business fit
Who this helps, and how:
Medical and health professional business owners: compare each day's visit notes against what was billed to catch missed charges before patients leave.
Local & serviceMechanics and tradespeople: check job notes against invoices so parts and labor that were done actually get charged.
Local & serviceLocal service businesses: flag recommended follow-up work that customers were told about but never booked.
Local & serviceIndependent contractors (barbers, bartenders, consultants): get a one-paragraph history of a client before each appointment.
Local & service
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Similar tools
Other tools for this job, and how they differ. Chosen by our editors, never paid for.
- ChatGPT
Can help prototype checklist and billing-gap scripts if you are not standardized on Claude.
- Cursor
Better when the practice tools grow into a real codebase you maintain over time.
- Shepherd (built-in features)
Stay inside the practice-management product for native reminders before adding custom AI.
“Strong evidence” (grade B) means: The person who did the work describes the setup and results in detail. How we grade. Spotted a mistake? Suggest a correction.