Build intelligently
Mobile engineering for the seams where apps actually break
Native iOS and Android work, the third-party SDKs embedded in your app, and the bridges between them and React Native, Flutter, or .NET MAUI. This is the work that gets escalated when a crash only happens in production and nobody can reproduce it.
Why do mobile SDK integrations fail?
Because nobody owns the seam. The SDK vendor blames the framework, the framework community blames the SDK, and the crash only reproduces on a customer's device. Diagnosing it means reading both sides: the native runtime, the bridge, and the shipped binary itself. Most teams have one of those skills, not all three.
Problems we solve
What this usually looks like from the inside
You're likely here because:
- A crash that only happens in production, on devices you cannot borrow.
- An analytics or payments SDK that works on native and breaks under React Native or Flutter.
- Memory climbing until the operating system terminates the app, with no obvious leak.
- A new OS version breaks something every September, and it is always a surprise.
- Nobody can say whether the numbers coming out of the app are actually correct.
What we build
Inside Mobile & SDK Engineering
Each of these is a definition rather than a label — if a term below is not what you thought it meant, that is worth a conversation before a proposal.
- Native iOS and Android development
- Applications built in Swift and Kotlin, including the parts that have to behave correctly under poor networks and real device constraints.
- SDK design and authorship
- Libraries meant to be embedded in someone else's application, where the host app's behavior is not yours to control.
- Cross-platform bridges
- Native modules and bindings for React Native, including the Fabric architecture, plus Flutter and .NET MAUI.
- Crash, hang, and memory diagnosis
- Root cause for concurrency races, main-thread deadlocks, and out-of-memory terminations, including symbolicating obfuscated crash frames.
- Production reproduction
- Reproducing a defect inside a shipping binary when the source is unavailable, using device-level instrumentation and proxy interception.
- Mobile privacy and data-exposure review
- Finding what an application leaks to embedded SDKs, webviews, and third parties, and closing it across platforms.
- OS readiness
- Testing against each year's iOS and Android releases before they ship, so a September launch is a check rather than an incident.
- Mobile telemetry and instrumentation
- Capturing what users actually do — layout, gesture, scroll, and state changes — without asking every product team to instrument it by hand.
How we work
Verify, rank, decide, prove
The same four steps on every engagement. Nothing is scoped until the current state has been checked against the running system rather than taken from a report.
Verify
We check the running systems and the live data ourselves before agreeing what to build, because a status report or a closed ticket is a claim rather than a measurement. One to two weeks.
Rank by reach
We count how many users, records, and configurations each problem actually touches, and that count sets the order of work rather than how large the fix looks. We try to refute our own findings first, and tell you which ones did not survive.
Decide in writing
Before building starts you get a written scope that separates what you asked for, what we chose, what we are assuming but have not proven, and what we are deliberately leaving out. Nothing starts on an assumption nobody agreed to.
Prove it moved
Work arrives in slices, and each one carries a before-and-after measurement of the thing it was meant to change, because a passing test shows only that the test ran. Two to four weeks per slice, closing with a written record of what was verified.
Technology we use here
Product names are used descriptively. We select against the problem, not against a reseller agreement.
- Swift
- Objective-C
- Kotlin
- SwiftUI
- React Native
- Flutter
- .NET MAUI
- Firebase
- Azure
How an engagement is packaged
- Engagement model
- Diagnostic engagement — one reproducible failure, or one integration
- Typical duration
- Two to six weeks
A diagnostic starts with a written root cause and the evidence behind it, whether or not we then build the fix. Longer platform and application work is scoped after that, because an estimate written before the cause is known is a guess. If your app is stable and the question is a new build, we scope it as an application engagement instead.
Questions
Mobile & SDK Engineering, answered
Do you build new apps, or only fix existing ones?
Both, and the second is the rarer skill. A new application is a well-understood engagement. Being handed an app that crashes for two percent of users, on hardware you do not have, with a stack trace that points at a framework rather than at the bug, is the work most teams cannot staff. We do that, and we write down what we found either way.
Can you work on an app you did not build?
Yes, and most of this work is exactly that. Reading unfamiliar code, instrumenting a running application, and reproducing a failure inside a binary rather than a project is a specific discipline. It is how a vendor's SDK team has to operate, because the applications the SDK runs inside belong to other people.
Our app uses React Native. Is that a problem?
No, but it changes where problems live. Every hybrid app has a seam between JavaScript and the native runtime, and that seam is where SDK integrations, threading, and lifecycle assumptions break. We have authored native bindings across React Native, including the Fabric architecture, plus Flutter and .NET MAUI, so the bridge is not a black box to us.
How do you know our analytics numbers are correct?
By checking rather than assuming. Mobile telemetry fails quietly: a payload silently dropped for exceeding a size limit, an event recorded with the wrong multiplier, a configuration that never reaches the device. None of those crash anything, so nothing alerts. We reproduce what the app actually sends, compare it against what the reports claim, and show you the difference.
Can you review our app for privacy and data exposure?
Yes. The common findings are an embedded SDK receiving more than anyone intended, user identity reaching JavaScript inside a webview, and personal data captured in screen recordings or logs. We report what leaves the device, who receives it, and what to change, with the fixes ordered by consequence rather than by ease.
Who owns the code you write?
You do, including anything we write inside your application or SDK. We hand over the diagnosis, the fix, the tests that hold it, and the reasoning, because a fix you cannot maintain is a deferred outage. Where a defect is in a third-party library, we give you a reproduction the vendor can act on.
Related reading
- Digital ExperiencesWebsites and portals that load fast, meet accessibility standards, and turn visits into conversations.
- AI & Intelligent ApplicationsAI agents, copilots, and custom applications that survive the move from a convincing demo to daily use.
- Cloud & IntegrationCloud architecture, APIs, and identity designed so failures are loud, retries are safe, and cost is predictable.
- The failures that don't announce themselvesThe dangerous defects in data and measurement systems are the ones that never crash. Nothing alerts, nobody files a ticket, and the wrong number is trusted for years.
Next step
Tell us what needs to change.
Describe the problem rather than the solution. We will tell you what we would do first, how long it takes, and what it costs.
We reply to every message, usually within one business day.
info@aqlyst.ai · (901) 232-2944