AI MVP Development for B2C Mobile & Web Apps

B2C apps live or die on the first session and the second week: activation, D1/D7/D30 retention, and paywall conversion decide whether your CAC ever earns back. Most consumer teams don't lose to a missing feature — they lose to a clunky onboarding, a generic feed, and a paywall that fires before the user has felt the value. SpeedMVPs builds production consumer apps as AI MVPs in 2-3 weeks: a cross-platform iOS and Android app (or an installable PWA), an adaptive onboarding flow, an AI-personalized core experience, and a subscription paywall wired to real attribution — shipped to a live TestFlight/Play track and the App Store, with 100% code ownership handed to your team.

Shipping a consumer app is as much a compliance exercise as an engineering one, because your two real regulators are Apple App Review and Google Play. We build to the App Store Review Guidelines that most first-time submissions trip on — 4.2 minimum functionality, 4.3 spam/duplicate, 3.1.1 forcing Apple in-app purchase for digital goods, 5.1.1 data collection consent, and the newer AI-generated-content and age-rating rules — plus Google Play's Data Safety form, Target API-level, and Families policy. If you offer any third-party social login on iOS, Apple's guideline 4.8 requires Sign in with Apple alongside it; we implement that by default. We also handle the privacy surface end to end: App Tracking Transparency (ATT) prompts and SKAdNetwork/SKAN 4.0 conversion values on iOS, Privacy Nutrition Labels and the Play Data Safety declaration, GDPR/CPRA consent via an IAB TCF-compatible CMP, and COPPA-safe age gating when under-13 users are in scope.

The stack is chosen to hit the 2-3 week window without cutting corners: React Native with Expo (EAS Build, OTA updates, Expo Router) or Flutter for one codebase across iOS and Android, and Next.js for a companion web app or installable PWA. We wire the integrations a real consumer app needs rather than a toy demo — RevenueCat over StoreKit 2 and Google Play Billing for subscriptions and free-trial paywalls; Firebase Auth, Supabase, or Clerk for auth including Apple/Google sign-in, OTP, and magic links; APNs and FCM (via OneSignal or Braze) for push; Branch or Universal/App Links for deferred deep linking and referral loops; and AppsFlyer or Adjust plus Amplitude, Mixpanel, or PostHog so your growth team can see the funnel from install to activation to trial on day one. Sentry and Crashlytics ship with it, because a crashing app is a churned user.

The AI is what separates a memorable consumer app from another CRUD wrapper. We build embedding-based personalization and feed ranking so the home screen adapts to each user, and adaptive onboarding questionnaires that turn a few taps into a genuinely personalized plan — the same pattern behind our AI fitness app MVP, where the intake flow generates a tailored training and nutrition program instead of a static template. For camera-first products we ship on-device and hybrid computer vision: our nutrition-scanner MVP turns a photo of a meal into logged macros, running inference through Core ML / LiteRT so it works offline, stays fast, and keeps image data on the device for privacy. Conversational features — an in-app AI coach, companion, or concierge — are built as tool-calling agents with streaming responses, grounding against your own data via RAG, and guardrails so they never invent facts a user would act on.

Retention and monetization are their own AI surface, and they're usually where consumer apps leave the most money on the table. We instrument churn-risk scoring, send-time optimization for push and lifecycle messaging, and paywall/experiment logic (Statsig or LaunchDarkly) so pricing, trial length, and hard-vs-soft paywalls are tested rather than guessed. For social and UGC-driven apps — feeds, profiles, chat, marketplaces — we add Trust & Safety from the start: LLM- and CV-based content moderation, report/block flows, and the transparency and notice-and-action mechanics the EU's Digital Services Act now expects from platforms hosting user content. Our social travel platform MVP is a working example of that mix: a consumer social graph, media-heavy feeds, and moderation running under real posting volume.

The engagement model is deliberately simple. Senior engineers scope your app in the first week — data model, screens, the one AI feature that has to be exceptional, and the store-submission checklist — then build, QA on real devices, and ship in the following one to two weeks. You get the full source repo, an EAS/Fastlane release pipeline, App Store Connect and Play Console assets and metadata, and a walkthrough with the people who wrote the code. There's no offshore relay and no vendor lock-in: with 100% code ownership from day one, your team can extend the app, swap the AI provider, or take it fully in-house whenever you choose. SpeedMVPs has shipped 18+ AI MVPs on this model with a team of 15+ engineers.

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