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Research report
AI Does Not Remove the Bottleneck
Find your real workflow constraints before buying AI tools.
An app is a client of your APIs, your data and your cloud. We build the mobile product and the system behind it as one job.
Clients we've worked with
Four phases from platform decision to store release.
Native versus cross-platform, argued from your roadmap and your team.
You getA platform decision record with the trade-offs written down
Interface work that respects each platform's conventions.
You getDesigns and a component inventory per platform
Sprints with device-lab testing and crash reporting from the first build.
You getInstallable builds every fortnight
Store submission, staged rollout and vitals watched at each step.
You getA live release plus a monitoring dashboard
Real engagements, described rather than named. Each leads with the number it moved and how that was measured.
Mobile engineers and backend engineers on one team, so the app and the services it depends on are designed together.
Products delivered
Years in business
Countries reached
Team members
It depends on what the product needs from the device. Heavy camera, sensor or background work, or a highly platform-specific experience, usually argues for native. A product that is mostly screens and data usually does not. We work it out against your roadmap in discovery and put the reasoning in writing, so the decision survives the people who made it.
Almost never. Shrinking a desktop product onto a phone produces something people open once. Mobile use is short, interrupted, one-handed and often on the move, so the question is which few tasks belong there and what they should look like away from a desk. That is the first thing we scope.
Yes, and it is an architecture decision taken at the start. Added later, it means rewriting the data layer. It means local storage, a sync strategy, conflict handling when two people change the same record, and telling the user plainly what has and has not saved. We design that up front because retrofitting it means rewriting the data layer.
By assuming nobody updates. Once an app is released you cannot recall it, and older versions stay on phones for months. So APIs are versioned, changes stay backward compatible, and anything breaking goes out behind a flag with a forced-update path held in reserve.
Where it removes typing or looking. Speaking instead of filling a form, photographing a document instead of transcribing it, getting a recommendation instead of searching. On-device keeps data private and works offline but limits model size; cloud gives you more capability and costs you latency and a network dependency. We pick per use case rather than as a policy.
Usually yes — we start with a short audit of the codebase, dependencies and release pipeline, then agree what to modernise first. A full rewrite is rarely the right first move; usually one or two parts carry most of the risk.
12 wks. We scope it in discovery and put the assumptions in writing, so both sides price the real work.
You do — code, App Store and Play accounts and signing keys stay in your name from the first commit.

They are very responsive and very open to ideas and feedback. When I have run out of ideas or don't know how to get past a roadblock, they have been very good with coming up with solutions.
