Most optometry practices 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 optometry practice is paying for the same problem to be solved twice.
Optometry practices · Applied AI
Built for the optometry practice 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
What gets in the way
The friction optometry practices hit that other industries don't.
- Optometrists balance eye tests, recalls, and frame sales, with recall reminders often the first thing to slip.
- Recall reminders and insurance or funding queries are the recurring admin load behind every optometry front desk.
How we build AI data analytics for optometry practices.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for a optometry practice business, so value lands before the build is finished. Ask your data in English.
Talk to usThe outcome for optometry practices
If we build the right slice first, optometry practices feel the difference inside the first month. 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
What's the realistic timeline for AI data analytics with a optometry practice?
Most optometry practices 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".
What does AI data analytics cost for a optometry practice?
Pilots start from a fixed scope priced to land a measurable result inside 6 weeks. Pricing depends on data volume, integration complexity, and whether you need us on managed services afterwards. We'll quote precisely after a 30-minute scoping call.
Anyone else in this space using AI data analytics?
Plenty. Owners check the business in 2 minutes instead of 2 hours. The interesting question is rarely "does it work" – it's "is your team ready to use the output." That's what we'd scope on the call.
What happens if we want to swap a vendor out later?
AI data analytics 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. DuckDB, Claude, Metabase, BigQuery, Vercel AI SDK 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.
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.