Service

Autonomous AI testing for mobile apps

Autonomous AI agents that exercise your iOS and Android app like a real user — exploring flows, healing assertions, and running stable regression coverage in CI. Built for teams done firefighting flaky Detox, XCUITest, and Espresso suites.

Promise
  • Exploratory agents that learn your app's flows on real devices
  • Self-healing assertions across native, React Native, and Flutter
  • Stable CI runs on BrowserStack, Sauce Labs, or your own device farm
  • Release smoke pack ready for every store submission

What you get

Agentic mobile suite

AI agents drive the app on real and emulated devices, building a regression pack that mirrors how users actually move through your product.

Device-matrix plan

A risk-weighted device + OS matrix — not 'run on everything'. We pick the matrix that catches 95% of field failures at a sane CI cost.

Flake triage rules

Network jitter, animation timing, and permission prompts are the usual culprits. Agents apply deterministic policies so flake stops being noise.

CI runner setup

GitHub Actions / Bitrise / CircleCI / Jenkins, wired to your device cloud. PR gate + nightly deep regression, with traceable evidence per run.

Release smoke pack

A pre-store-submission suite that hits payments, auth, push notifications, and deep-link flows — the things that break user reviews when they regress.

On-call QA lead

A named senior engineer owns your suite end-to-end and is reachable during your release windows.

How it works

  • Exploratory agents drive the app on real devices, log reachable states, and identify revenue-critical flows
  • We pair output with a senior mobile QA lead to prioritise — auth, payments, push, deep-links, and the journeys your support team sees break most

Evidence you will actually see

Per-run video + step-by-step trace for every device in the matrix
Self-healing change-log — every locator and timing rule the agent adapted
Trend snapshots: pass rate, flake rate, runtime, store-submission time-to-green
Failure clustering by device, OS version, and flow — so platform bugs surface fast

Release with confidence on every device that matters.

Tools & stack

Appium + agentic layer

Cross-platform engine for iOS and Android; the agent layer drives exploration, self-healing, and intent-based assertions.

XCUITest / Espresso

When you need native-grade speed and depth — agents wrap your existing native suites, no rewrite.

Detox / Maestro

For React Native and cross-platform teams that already invested in JS-native or YAML-flow tooling.

BrowserStack / Sauce Labs / Firebase Test Lab

Real-device runs at scale; we wire the runner, not just the scripts.

GitHub Actions / Bitrise / CircleCI

PR gates and nightly regression integrated with your existing mobile CI.

Jira / Linear / TestRail

Traceability from critical flow → test → device run → ticket, with attached video evidence.

FAQs

What does 'autonomous AI testing' actually do for a mobile app?+
Agents drive your app the way a real user would — they explore screens, learn the flows, and propose what should be in regression. They also adapt assertions when copy, layout, or animation timing changes. The underlying engine is still Appium or XCUITest/Espresso, so runs are deterministic and CI-friendly.
Do you support React Native and Flutter, or only native iOS and Android?+
Both native and cross-platform. We run React Native via Detox or Appium, Flutter via integration_test or Appium with semantics labels, and native via XCUITest/Espresso. The agentic layer is the same in each case.
How do you handle real-device costs?+
We help you size a risk-weighted device matrix — usually 6–10 devices covering the OS versions and form factors that catch ~95% of field failures. PR-gate runs go to emulators; only nightly and pre-release runs hit real devices.
We have a flaky Detox suite. Do you start over or fix it?+
We fix. The agentic layer wraps your existing suite, applies deterministic waits and stable locators, and quarantines tests that are genuinely broken. Most teams see flake rate drop 60–80% before we add a single new test.
Can you also test the web product on the same engagement?+
Yes — many clients pair mobile with our /services/ai-web-application-testing/ or run both under our broader /services/agentic-ai-qa/ programme.
How do you handle biometric, push, and deep-link flows?+
Biometrics via the platform's test prompts and stub providers, push via Firebase / APNS test channels, deep links via the agent constructing valid URLs and verifying the destination state. All three are part of the standard release smoke pack.
Proof · Case studyMobile QA: 474 green tests, two blind spotsRead the case study
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