Web Applications
An AI-powered system that automatically crawls websites, analyzes performance, and generates optimization recommendations.
What it does: Concurrently crawls websites to extract metadata, measures page performance, and produces AI-driven recommendations for SEO improvements. How it was built: Java + Spring Boot backend, PostgreSQL with Liquibase migrations, Playwright for browser-based crawling, Docker for containerization, and OpenAI + Google PageSpeed APIs for AI analysis. What I learned: Building scalable concurrent crawling pipelines; integrating multiple third-party AI/analytics APIs; improving system throughput and reliability through asynchronous processing and containerized deployments.
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