Root Cause Engine
AI-powered root cause analysis engine that correlates crashes, ANRs, CI failures, and deploy logs — pinpointing the exact commit or config change that broke production.
Resolution Time
Data Streams
Manual Triage
The Challenge
Debugging production crashes in a complex hybrid mobile application was a tedious task. Software engineers had to correlate telemetry from crash reports, continuous integration logs, container metrics, and code repositories to find the cause of a bug, slowing down critical hotfixes.
Our Solution
We engineered a centralized Root Cause Engine. Using machine learning semantic matching, the engine ingests real-time exceptions and cross-references them against recent code modifications, environmental configurations, and microservice status. It provides a visual line-by-line breakdown of the issue.
Interactive System Architecture
Log Ingestion Hub
Created unified queues to process data feeds from Datadog, Sentry, and GitHub APIs.
ML Commits Map
Configured text embedding models to map stack traces to code commits and commit summaries.
Visual Root UI
Designed an interactive timeline detailing the actions that led up to the outage.
Project Gallery & Mockups
The Business Impact
Reduced the time needed to identify the root cause of high-priority issues from hours to under 2 minutes. The system has automatically triaged thousands of incidents, eliminating manual tracking efforts.
Project Details
React Native App
4 Months
Core ML & System Engineers