AI-Driven UI-Based App Testing

Preview coming soon

The problem: UI and app regression testing stays brittle, manual, and slow to maintain.
What I built: AI-driven, UI-based automated app testing that adapts to interface changes.
What it shows: Bringing AI to the QA discipline scaled at OEM level, releases 4 → 26 / year.

UI regression testing breaks the moment the interface moves, which is why so much of it stays manual and expensive to maintain. This tool brings AI to that exact problem, UI-based automated testing that adapts to interface changes, applying the QA discipline that scaled releases 4 → 26 a year at OEM scale. Currently in development.

App Competitor Benchmarking Tool

What it does: Systematically benchmarks a mobile app against named competitors across features, UX patterns, release cadence, store ratings, and capability gaps, replacing ad-hoc, quickly-stale manual teardowns.

Self-initiated See the build

Method

In use

AI-Native SDLC with Human Gates

The problem: AI can accelerate software delivery, but unguarded it erodes the rigor that regulated, safety-relevant automotive software demands.

Self-initiated See the build

Method

Framework

Hyperpersonalization for Mobile Ecosystems

The problem: Connected-vehicle and mobile ecosystems hold rich entitlement and behavioral signal but mostly ship one-size-fits-all experiences.

Self-initiated See the build

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