Most veterinarians we talk to aren't short of dashboards or tools – they're short of an hour back in the week. That's the lens we put on AI data analytics: not a tech showcase, but a careful look at the one or two workflows where a veterinarian is paying for the same problem to be solved twice.
Veterinarians · Applied AI
Built for the veterinarian who's already tried the off-the-shelf option and bounced off it.
What AI data analytics actually does
Stop digging through dashboards. Ask plain-English questions of your sales, jobs, and customer data – get charts, summaries, and the why behind the numbers in seconds.
- 01 Natural-language queries over your Xero, Shopify, CRM data
- 02 Weekly auto-summaries delivered to inbox or Slack
- 03 Anomaly detection – flags weird weeks before you notice
- 04 Forecasts that explain themselves, not black boxes
Built on: DuckDB Claude Metabase BigQuery Vercel AI SDK
Without Kiwi Dynamics
With Kiwi Dynamics
Lay of the land
The two or three things that decide whether this works for veterinarians.
- Vet clinics run on bookings, recalls, and after-hours emergency calls, with a small front-desk team trying to do all three at once.
- Between surgery schedules, vaccine recalls, and owners calling mid-panic, the phone and the inbox are where clinics lose the most time.
How we build AI data analytics for veterinarians.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for a veterinarian business, so value lands before the build is finished. Ask your data in English.
Talk to usThe outcome for veterinarians
We'd call the engagement a success when veterinarians are using the system without thinking about us. Owners check the business in 2 minutes instead of 2 hours.
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.
Questions
FAQ
How fast could we have AI data analytics in production?
Eight to ten weeks for most veterinarians. Faster if your data is in good shape and slower if we're untangling a legacy integration first. We'll give you a realistic number on the scoping call rather than the optimistic one.
What's the smallest engagement you'd take on?
A two-week paid discovery for veterinarians that aren't sure whether the build is worth doing at all. You get a one-page write-up of what we'd build, what we'd skip, and what it would cost. About 30% of those discoveries end with us recommending you don't proceed.
Can you walk us through a comparable build?
Yes – on the first call we'll pick the closest engagement we've shipped to what you're describing and walk through the outcome, the headcount and the time it took. Owners check the business in 2 minutes instead of 2 hours.
What if our veterinarian doesn't have any data ready?
Most don't. Getting the data into shape – ingestion, cleaning, the lightweight contracts you need before any model is useful – is part of the engagement. For AI data analytics specifically, we typically run that work on DuckDB, Claude, Metabase, BigQuery, Vercel AI SDK and assume messy starting conditions from day one.
One reply, one direction.
We don't run sequences or follow-up automation. One useful answer, one decision on your side.
Get in touch
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.