You have an idea for an AI product and no engineering team. You want the whole thing: an app people can download, an AI feature that is actually good, a way to charge for it, and it live in the App Store and Google Play — not a Figma file and not a landing page with a waitlist.

You want one person accountable for all of it, rather than a mobile contractor, a backend contractor and an "AI consultant" who each blame the other two.

The app. Flutter, so it is one codebase for iOS and Android, with native Swift where the platform demands it — camera work, health data, anything the cross-platform layer does badly. Not a no-code wrapper: real code you own, that a future engineer can pick up.

The backend. Supabase and PostgreSQL, with Python services for the work that does not belong in a database. Auth, storage, the data model, and an API your app is not the only possible client of.

The AI. LLM pipelines built as explicit graphs on LangGraph, not a prompt in a loop — so failures have a location and retries live in one place. Retrieval over your users' own data where that is the point. Evaluation on a reference set from day one, full tracing, and cost ceilings, because token spend is a line item in a subscription business.

The money. Subscriptions across the App Store, Google Play and, if you want it, a direct web checkout — with one source of truth for who is actually paid, webhooks handled idempotently, restores that work, and reconciliation that catches silent leaks.

The release. Store listings, review submission, and the parts of App Store and Play compliance that reject first-time submissions. CI/CD so the second release is not as painful as the first.

Because I have shipped this exact stack as my own product, not as a deliverable.

F/AI is an AI fitness trainer I co-founded and run as CTO. Flutter and Swift, Supabase and PostgreSQL, LangGraph pipelines, billing across three sources. It has 340,000+ registered users, 23,000 monthly actives, $8,000 MRR, 2,000+ paid subscriptions and 4.5★ on the App Store. I wrote the first production version alone. The user counter is public at fitgpt.pro/stats.

That means the estimate I give you is not a guess about how long store review takes, or what CV inference costs at scale, or which part of billing goes wrong. I have already paid for those lessons.

Fixed price against a written scope, agreed after a proper conversation about what you actually need — the $12,000 is a starting point for a real product, not a placeholder. You see builds as they happen. You own the code and every account from day one; nothing is hosted on something only I can log into. Frankfurt, Germany (CET), English, calls whenever you need them.