AI features in your React Native app.
Shipped, not stuck in review.

That is the work we do most. Streaming chat that survives a bad connection, camera and vision features, voice, retrieval over your own data, and moving the model call off the device where the API key does not belong. We start with the audit so nobody quotes a number before seeing the code.

Not for having AI in it. Apps get rejected for what sits around the feature: user-generated content with no moderation or reporting path, an age rating that does not match what a chatbot can say, permissions requested without a visible reason, data sent to a model provider that the privacy labels do not declare, and subscription screens that do not spell out what the AI actually does. We prepare for all of those before submission. Nobody can guarantee an approval, and anyone who does is selling you something.

Mobile is the focus: React Native and Expo, including native modules in Swift and Kotlin when a vendor SDK has no wrapper, and App Store and Play submission. We also build the web apps and backends behind those products. See the services pages for the specific scopes.

Both, and the tests are part of the fixed price rather than a line item you can cut. Unit and integration tests on the logic that is expensive to get wrong, end-to-end tests on the flows that make money, and both running on every pull request so a regression fails CI instead of failing a customer. On mobile that means Detox running from EAS Workflows against a real build before a submission, because a regression there costs a review round. We use AI to widen what gets tested: it generates the real-world cases nobody sits down and writes, like the interrupted upload, the expired session mid-checkout, the retry that arrives after the timeout, the pasted emoji in a name field. A senior engineer decides which of those a real user could actually reach, and the rest are thrown away. What we do not do is chase a coverage percentage.

Yes, if that is needed before you share project details.

Yes, deliberately. We use Claude Code, Codex, and GitHub Copilot to move faster through boilerplate, migrations, and test coverage, and to generate the real-world edge cases a person would not sit down and enumerate. What we do not do is skip the parts AI cannot own: architecture decisions, security review, and judgment about what production-ready actually means for your users. Every AI-assisted change ships through senior review, not blind acceptance of the first output. That review step is the whole business.

That is fine. We also build products from scratch for people who have never used an AI builder, and take standard web, mobile, backend, and AI projects. The builder list is the entry point, not a restriction.

Small and medium ones: a single product, owned by a small senior team. We are not set up for large, multi-team enterprise platforms.

Core offers are fixed-price. Hourly work is possible for agency subcontracting or genuinely undefined scope.

You get handoff, documentation, and an optional monthly support path after launch.