One system between “someone should fix this” and “it’s live and measured.”
The AppDNA platform is an App Growth OS for subscription mobile apps: nine growth modules on one event pipeline, an experiments engine with human approval and automatic guardrails, and a server-driven SDK that renders paywalls, onboarding, messages, and surveys natively on iOS, Android, Flutter, and React Native — so changes go live without an App Store release.
Connect. Learn. Execute. Compound.
Installed in under an hour. Reads RevenueCat, Adapty, Firebase, AppsFlyer and the rest on day one — zero migration.
Audits all nine modules, maps the funnel, benchmarks apps like yours, finds the biggest leak — with reasoning attached.
Live natively in minutes — new paywall, step, or message — at 10% traffic, stop-loss armed. No release, no review.
Every outcome — win, loss, inconclusive — makes the next proposal smarter about your app. It never resigns.
The system proposes. You approve. It ships. It learns.
The full funnel in one place.
Nine modules, one event pipeline underneath — that is the point: when everything shares one pipeline, the system catches what point tools structurally can’t, like your onboarding change moving paywall conversion. Each module has its own specialist agent watching your data around the clock, diagnosing, and drafting the fixes that land in the Insight Inbox. They watch and draft; every change waits for your approval; the SDK ships it. A specialist on every module — and this team never resigns.
Know exactly who converts and why; every other module inherits this context.
Store listings that test themselves — titles, screenshots, descriptions, grounded in your category.
Native flows edited visually and shipped instantly — reorder steps, move the permission ask, no release.
Composable paywalls — 30 templates, 24 section types — plus price and trial tests, rendered natively.
Journeys, push, in-app, and email in one orchestra, triggered by real funnel behavior.
Campaigns across 9 ad platforms — with spend decisions that see all the way to revenue.
Content pillars, schedules, and analytics for the channels that compound.
NPS, review sentiment, surveys, and the Love Score — complaints become experiment proposals.
Landing funnels and web checkout revenue — the fastest route around store fees, same pipeline.
Plus the shared engine underneath all nine: full-lifecycle experiments with guardrails, SRM detection and automatic winner analysis, the Insight Inbox, and the copilot.
Approve like email. The system ships.
Safer than build → submit → hope.
Why the same question gets a different answer for your app.
Generic AI gives generic advice because it has generic context. AppDNA answers from five layers, each narrower and more yours than the last.
Layer five is Growth Memory — the moat you build for yourself. Every experiment, win or loss, becomes structured learning in your workspace. People can leave; the learning stays.
On Autopilot and Enterprise the agents work to your playbook — every change still waits for your approval. The market’s lessons become yours. Your lessons stay yours.
Your data never trains a shared model and is never visible to other customers — isolation is enforced in code, not policy.
Chat is the interface. The system is the difference.
Agentic mode (Autopilot): flip from “it proposes, you approve” to “it works your way, inside guardrails you set.” Opt-in per module, reversible any time, every action in the audit trail. A chat that ships experiments is growth.
Strategy stays human. Execution becomes automatic.
Complete on its own. Compatible with everything you already run.
AppDNA runs your entire growth operation by itself — and doesn’t ask you to rip anything out to start. It reads billing and events from your existing stack on day one, zero migration. Over time you’ll simply need fewer subscriptions. Your call, your pace.
Your engineers can vet everything.
The growth lead loves it, then one Slack message from engineering decides the deal. Fair. Here’s the ten-minute verification path.
One dependency, a three-line init, an API key. The quickstart is public.
SwiftUI and Jetpack Compose. Offline-safe caching keeps a working app with no connection.
Public APIs only — server-driven config, the pattern the biggest apps use.
A normal dependency. Delete it and your app builds and runs; nothing core depends on us.
Five questions practitioners ask once they’ve seen the loop.
01Do I need a data team to use this?
No. The system does the analyst work — funnel mapping, experiment analysis, SRM detection, winner calls — and explains its reasoning in plain language on every proposal. If you have a data team, they get query access; if you don't, that's precisely the gap the platform fills.
02How fast is a change actually live?
Minutes after approval. The SDK pulls the new configuration and renders it natively — no build, no submission, no review queue. The full cycle typically runs 1–2 weeks with one person, against an industry norm of 3–6 weeks with 4–6 people.
03What happens to users offline or on old versions?
They keep a working app. The SDK caches the last known-good configuration, so no connection means no change — never a broken screen. Rollbacks work the same way: instant on connected devices, safe everywhere else.
04Can the system change my app without me knowing?
No. On Starter and Pro every change is approval-gated. In Autopilot's agentic mode it operates only inside guardrails you configured, opt-in per module, and every action lands in the audit trail. You can always answer “what changed, when, and who said yes.”
05Which platforms does the SDK support?
iOS, Android, Flutter, and React Native. Everything renders natively per platform — SwiftUI on iOS, Compose on Android — not webviews.
Missing your question? Ask us directly — a human replies within one business day. Engineers: read the docs →
See the system loaded with your app’s data.
The free audit is the platform’s Learn step, run on your store listing — Growth Score, module scorecards, your biggest leak, a 90-day plan. Then one click configures your entire workspace from it.
