A while back we put our vehicle maintenance database on the open web, with factory service schedules and cost estimates for over a thousand cars, free, no app required. It worked well enough that we did the same thing for every app that had a dataset worth sharing. This post is about that pattern, because it has quietly become how we think about building.
The pattern
Most of our apps are, underneath, a structured dataset plus a private place to track your own copy of it. Garage Story is a maintenance database plus your car’s history. Fluency is a library of reading passages plus your own progress. The care apps are recurring-task schedules plus your own log.
The dataset is useful on its own, before you install anything. So we publish it twice:
- As an app: private and offline-first. Each app explains its own storage: some offer private iCloud backup or sync, while Fluency keeps its reading record locally. It remembers your car, your home, or your reading.
- As a free web tool: related structured data from the same source pipeline, as plain pages anyone can read, no account and no email gate. The public collection can grow beyond the smaller, curated library currently shipped in an app.
What’s on the open web now
The free tools live here, all built from structured sources shared with the apps:
- Vehicle maintenance schedules: over a thousand cars, motorcycles, and RVs, with intervals and U.S. shop costs
- Home maintenance and boat checklists: what to do, how often, what it costs
- Dog and cat care schedules in one pet hub, plus a houseplant care guide
- Reading practice: 651 passages with 2,616 comprehension questions, answers, and explanations
No paywall, no signup. The web collections may be broader than an app’s curated offline library; where the counts differ, each product page states what that app currently includes.
Why give it away
Two reasons, stated plainly.
First, the information should be easy to find. A factory maintenance schedule lives in your owner’s manual and almost nowhere pleasant to read; a good reading passage with real questions is buried under ad-heavy worksheet sites. We already had the structured data, clean and checked. Publishing it costs us little and helps anyone, app or no app.
Second, to be blunt: we make the apps. A web page tells you what a 2015 Outback needs; Garage Story tells you when yours needs it and remembers what you’ve done. If the free pages are useful, some readers will want the version that does the remembering. That is the whole deal, and we would rather say it out loud than pretend the pages are charity.
One engine behind all of them
The part that makes this work as a two-person studio: we did not build ten websites. We built one small engine that turns a dataset into pages: a schedule becomes a table with intervals and costs, a task list becomes a checklist, a passage becomes a practice page. Each app just plugs its data into it. Adding the next app’s free tool is mostly a matter of pointing the engine at new data.
That is the same principle as the apps themselves: do the structural work once, then let data fill it. It is why a very small team can keep a fairly wide shelf.
What’s next
More apps are on the way, and each one that ships with a dataset of its own will get its free public version too. When we expand or correct a public source collection (new models, revised intervals, more passages), the pages update at the same addresses. Apps can adopt those updates on their own release schedule and may keep a smaller curated subset for offline use.
If you find an error in any of it, tell us; it fixes the page and the app in one go.