Case study · appdevelopmentcostcalculator.com
An app cost model, from domain to gated release in under 22 hours
Four timestamps, all checkable
- 012 Oct, 11:32 UTCDomain registeredVerisign RDAP
- 022 Oct, 12:39 UTCFirst 15-page build live on its preview hostgit 8b1ef33663
- 032 Oct, 22:44 UTCLive on appdevelopmentcostcalculator.comgit a24258aa79
- 043 Oct, 09:06 UTCEngine and 87,048-assertion gate shipped, gate passinggit 3e408c2b75
From registration to the commit recording the gate passing on the deployed site: 21 hours 34 minutes. The name was chosen that morning by a domain hunt that measured search demand first: 320 searches a month in the US for "app development cost calculator".
A calculator with two hour models, and the pages around it
The calculator takes the inputs a buyer can answer: platforms, size, features, integrations, backend, design depth, AI features, and who builds it. It returns hours by category, a cost band, a timeline and a first-year running cost, with the rate source and its read date printed underneath.
It prints two columns. One is built AI-native, the way we work. The other is what agencies typically quote. Each comes from its own tables, so the gap between them is a result you can inspect rather than a percentage someone typed in:
| Category | AI-native | Agency quote | AI-native agency |
|---|---|---|---|
| Design | 84 | 139 | |
| Build (code) | 121 | 399 | |
| Integrations | 74 | 148 | |
| Code review and hardening | 53 | none | |
| Testing across devices | 109 | 109 | |
| Store release | 26 | 26 | |
| Project time | 64 | 82 | |
| Total hours | 531 | 903 |
Across the eight example apps, the AI-native column comes to 54% to 61% of the agency hours. You can try your own scope at appdevelopmentcostcalculator.com.
If a figure has no source, it is not on the site
Every rate, fee and model price lives in a fact file with its publisher, URL, read date and the quoted sentence it came from. Wage data comes from the US Bureau of Labor Statistics; agency rate bands from Clutch and Accelerance; store fees from Apple and Google; model prices from Anthropic, OpenAI and Google.
Some figures the industry repeats did not survive that rule. Freelance marketplace rates could not be read at source. No neutral source with a stated method was found for the common "maintenance costs X% of the build each year" rule, so the site does not use one. Those gaps are listed on the site's own sources page instead of being filled with guesses.
87,048 assertions, run against the engine the site runs
The gate imports the same engine file the live site uses and checks it from five directions. It prints what it read, so a run that silently read nothing cannot pass:
- 35
- facts, each with publisher, URL, read date and quote
- 33
- source files scanned for fact references
- 19
- built pages read as a visitor would see them
- 102
- fixture entries: every example-app figure
- 7,776
- boundary runs across the input space
Facts
Every rate band, model price and in-house rate equals an independent recomputation from its source fact. Figures listed as not sourced appear only on the disclosure list and in one sentence that attributes them.
Arithmetic
Lines sum to the total. Low ≤ mid ≤ high. The check fails if adding a feature lowers the hours, or if team size moves the cost rather than the timeline. Running cost equals upkeep plus fees plus twelve months of AI usage.
Pages
The homepage examples, the estimate card and the guide-page leads print exactly what the engine computes.
Independence
The AI-native column is computed from its own tables. There is no speed-up multiplier linking it to the agency column, and the gate fails if one appears.
Honest labels
A category tagged “no change” must carry equal hours in both columns. One tagged “compressed” must be at most 75% of the agency figure.
A label that disagreed with its own numbers
On its first run the gate failed 16 times, all from one cause. The calculator tagged "testing across devices" as a category AI does not compress, but the agency column computed testing as a share of its larger build hours. So the two columns showed different testing hours for the same app, under a label saying they should match. A footnote explained it, which is the kind of explanation a reader should not need.
The fix gave both columns one shared, bottom-up testing and release table. It went in as its own commit, labelled as a fix, and the methodology page records it as a correction. The agency figure for the default app moved from $65,000 to $67,000 at the site's US agency rate; every example stayed inside the published agency ranges the site cites. The AI-native figures did not change, which we confirmed character by character on the live site after the deploy.
The same method, on your product
A client build gets the same treatment: the facts it depends on held in one place with their sources, a gate that checks the arithmetic and what the screens print, and fixes made in labelled commits you can read. It is how a small team working with AI agents ships quickly without shipping guesses.
Start a conversation
Send us a scope, or a link to your numbers in the model. We reply with questions or a quote.