LLM evaluation suite for Doctor AI
A RAG-based evaluation framework that tests Ultrahuman's Doctor AI feature and catches regressions, hallucinations and drops in answer quality.
~/projects
A selection of things I have built and worked on.
A RAG-based evaluation framework that tests Ultrahuman's Doctor AI feature and catches regressions, hallucinations and drops in answer quality.
Web and mobile UI automation that uses AI and MCP to find elements and repair itself, reducing the maintenance that test suites normally need.
Automation for video playback at Disney+ Hotstar across web, Android and iOS players, on the squad responsible for streaming quality for 28M+ concurrent users during peak live events.
Quality engineering for an AI feature that reads blood test reports, from PDF ingestion, through AI analysis, to what the user sees in the app.
A Karate-based API automation suite that runs in Docker, with an AI-driven system that generates consistent, realistic user data for staging and QA.
Company-wide Grafana and Prometheus dashboards showing real-time test analytics and Appium failure tracking for every squad.
Web, mobile and API automation for the 100ms live video conferencing SDK, including Flutter-based mobile automation frameworks.
Three semester projects at R. V. College of Engineering, including leading a team through the end-to-end build of a hardware-based solution.