Why the Kotzilla Platform?

Debugging and fixing production issues in Android and Kotlin Multiplatform apps today relies on three categories of tools, each with a significant blind spot:

1. Android Studio Debugger: While natively integrated into Android Studio, it can be intrusive and challenging to use for complex applications. Developers need to manually add breakpoints, which can be inconsistent in highly optimized code. Debugging multithreaded interactions is difficult, and the debugger's performance impact makes it not usable in production environments.
2. Observability and APM platforms: Often designed first for backend systems and extended to mobile, these tools detect production symptoms but not always the root causes behind them. Understanding why a screen is slow or why an ANR fires requires extensive manual logging around component lifecycle, dependency resolution, and multithreaded execution. Root causes are inferred statistically from unstructured logs, which is why AI layered on top has to guess.
3. AI coding agents: Generate code from training data and pattern matching, but are blind to production behavior. Without access to real session data, dependency graphs, or causal context, agents produce plausible fixes rather than grounded ones, and the hardest bugs (ANRs, startup regressions, memory churn) stay unresolved.

The Kotzilla Platform is AI-Native Developer Observability for mobile apps. It unifies, crash reporting, debugging and performance monitoring across development and production, and gives AI coding agents the production context they are missing, so fixes are grounded in real session data instead of guessed from patterns. It helps you quickly detect and resolve issues like:

• User-impact issues: Detect the problems that degrade user experience and impact revenue: crashes, ANRs, slow cold and warm startup, and slow screen rendering.
• Component-level root causes: Pinpoint the architectural and runtime drivers behind those symptoms: slow dependency resolutions, heavy constructor work, complex dependency graphs, lifecycle misuse, multithreaded performance bottlenecks, and excessive memory usage caused by frequent component recreations. Kotzilla links each user-facing issue back to the specific components causing it.
• Unified crash debugging across targets: Investigate crashes in Android apps, Kotlin Multiplatform targets (iOS, Desktop, JS, WASM), and SDK libraries, with symbolicated iOS stack traces and the full Kotlin stack trace on every target.

Key benefits

Symbolic, not statistical

Most observability tools infer root causes from unstructured logs and traces, which is why AI layered on top has to guess. The Kotzilla Platform captures app structure (dependency graph) and behavior (runtime metrics) as one connected model, with context preserved from capture to analysis. Root causes are computed, not inferred, and every fix prompt sent to an AI agent carries the full causal chain.

Automatic data capture, no overhead

One of the biggest challenges in performance monitoring is gathering the right data. But with the Kotzilla Platform, that's handled automatically. The platform taps into Koin's container to capture essential app behavior data without the need for manual instrumentation. This gives you a comprehensive debugging and performance monitoring experience in both debug and release builds with minimal overhead.

AI-native remediation

Connect your AI coding assistant to Kotzilla through the Kotzilla MCP Server. Real session context (dependency graphs, resolution timings, crashes) combined with proven Kotlin fix patterns let the assistant go from detecting an issue to applying a fix directly in your project, without leaving your code editor or terminal.