aso engine · finds the best keywords for your specific app
free beta starts july 29, 2026
App keywords, measured.
Make your app the one people find in store search.
Feed it a plain-text description of your app. It returns ranked keywords plus a title, subtitle and keyword field — and every number expands to the raw store response it was computed from.
Free during beta. No card. The app runs on your own machine.
new apps shipped in one major store alone in 2025.
source: Sensor Towergrowth in app submissions, quarter over quarter.
source: Sensor Towerof installs start with in-store search.
source: platform data, 2025The stores are flooding. Search is still how users find you. Metadata is the only distribution channel you fully control.
One pipeline, five steps —
each signed by who does it.
The AI's role is deliberately narrow: it reads your brief and proposes keyword hypotheses. Everything measured — demand, difficulty and relevance — is computed by code, from live store data.
Brief in
youA plain-text description of your app: what it does, who it's for, what it is not. Two minutes. That's the only input.
Context extraction
AI · judged by youJobs-to-be-done, user vocabulary, and anti-semantics: what your app must never rank for. You review and correct before anything runs — the pipeline's only checkpoint.
Hypotheses, grounded in the store's suggest graph
AI + codeThe AI proposes keyword hypotheses from your brief; each is expanded against the store's live suggest graph — completions, continuations, alphabet-soup. Only phrases the store itself suggests to real users survive, so no raw model-invented phrase ever reaches scoring.
Measurement
codeP from probing live autocomplete, D from the live top-10, R from the keyword's measured share of the in-niche results. All three are computed by code from live store responses — the AI produces no score.
Set-cover layout
codeWords distributed across title, subtitle and the 100-char keyword field with zero repeats. The second indexed localization (es-MX for a US listing) is filled automatically.
Ship-ready metadata
Title · subtitle · 100-char keyword field · second localization · full research trail.
Audit every number.
The industry sells "popularity scores" without saying where they come from. Below is every formula this tool ships with. Each parameter is measured, logged, and traceable to the request that produced it.
PDemand, from autocomplete probing
The phrase is typed against the store's live autocomplete character by character. Recorded: the prefix depth where it first appears (earlier = stronger demand) and its rank in the list. It's the store's own demand signal, read directly.
DDifficulty, from the live top-10
For every keyword the actual search results are pulled, and each of the ten apps you'd fight is scored for strength — weighted by its position on the page. A top-10 full of dead apps is an open door, and you will see it.
+ 0.15·freshness + 0.25·exact-match)
volume — review count; quality — rating; freshness — time since last update; exact-match — the keyword verbatim in a competitor's title.
RRelevance, measured from the store's own results
Relevance is not an AI opinion. Code measures how much the keyword's live results actually overlap with your niche — its share of the in-niche results — and adjusts for semantic fit to your confirmed brief. Every input is a live store response you can open; the result is a 0–3 value that is computed, not guessed.
ΣOne score per keyword
Demand and ease are combined as powers, not a sum, on purpose: a keyword nobody searches is worth zero no matter how easy it is, and a keyword you can't crack is worth zero no matter how popular. Relevance scales the result linearly.
If a number can't be traced to a raw store response, it doesn't ship.
We measured what others assume.
The engine's rules come from live store data, not habit. Three findings that shaped it — each one checkable from your own keyboard.
Share of raw keyword candidates that turn out to be real user queries: phrases an LLM invents outright versus phrases grounded in the store's suggest graph. Measured on 828 probed keywords across two niches. This is why we never ship a raw model-written phrase — the AI's hypotheses are expanded and validated against the store's live suggest graph, and only phrases the store actually suggests survive.
probe any LLM-written keyword list against store autocomplete and count the hitsStores seed app names into autocomplete — including apps with zero ratings. So the name of a dead app looks exactly like a high-demand keyword. Every phrase is cross-checked against its own top-10: an exact name match on a weak app gets its score zeroed, with the evidence attached to the row.
type the name of any abandoned app into store search — it still autocompletesQuestion-style and four-plus-word phrases from our probes that turned out to be real queries: zero out of 102. People do not type questions into store search. Your character budget goes only to queries that exist.
type any "how do i…" phrase into store search and watch the suggestions stay emptyShip-ready metadata, with receipts.
Title and subtitle from real queries
Assembled from whole top-scoring phrases, so they read like people talk. Your best phrase goes into the title verbatim.
A packed keyword field
Set-cover optimized: no word repeated across any field, coverage report showing which queries each field wins.
The second indexed localization
Stores index extra locales per storefront. Most listings leave it empty; a run fills it, guaranteed non-overlapping.
Full research trail
Every probed keyword with P, D, R and score — sortable, filterable, exportable, re-runnable from cache.
Download ASOptimus.
The beta hasn't shipped yet — these buttons switch on at launch, and waitlist invites go out first. One download, one activation key from your inbox, and your first run is going.
At launch each button asks for exactly one thing — your email. Use a real one: the activation key is delivered there.
The deal, plainly.
You get
- Full runs, free, for the whole beta period
- Runs on your own machine — every App Store request goes from your device, not our servers
- Founding price locked when paid launch happens
- A direct line to the author — fixes ship in days
We ask
- Run it on a real app you ship
- 15 minutes of honest feedback after the first run
- Optional: a before/after case with numbers
devs with a live app in the store get onboarded first
One dollar, one credit.
Free during the beta. After launch: prepaid credits, debited per verified keyphrase while a run works. No subscription — between runs you pay exactly $0.
custom amounts work at the same $1 = 1 credit rate · beta testers keep founding pricing
Is it actually free?
During the beta — yes, fully. After launch it becomes pay-per-run credits, not a subscription: app store optimization (ASO) is episodic work, and a subscription would mostly bill you for the months you don't touch it. Beta testers keep founding pricing.
Where does my data live?
The app runs on your own machine, and all store traffic (autocomplete probes, live top-10 pulls) goes directly from your device — we never proxy it. Your account, runs and results are stored in your account so you can resume and review them; email us from your account address any time for a copy or full deletion. The only other call that leaves is to our AI provider, which turns your brief into keyword hypotheses.
What exactly does the AI do — and not do?
It extracts product context from your brief (which you confirm) and proposes keyword hypotheses to explore. It never produces a score — demand, difficulty and relevance are all computed by deterministic code from live store responses you can open.
Why trust your scores over the big tools?
Don't trust them — check them. The formulas are printed on this page, and every number in a run expands to the raw store response it came from: the exact prefix and rank for P, the ten apps behind D, the in-niche results behind R.
Which storefronts?
20 storefronts at beta start, US included, each with the correct extra-locale pair. The semantic language is configured separately — for example Spanish-language semantics for the US store.
When do I get in?
Onboarding goes in small batches so every tester gets real attention. Earlier signups go first; devs with a live app in the store skip the queue.
Metadata you can audit.
Free during the beta. Small batches, live apps first.
Free during beta. No card required.