Enabled users to register game IDs across multiple games, allowing automated tracking of player data. Leveraged local text-to-speech and large language models (LLMs) with Retrieval-Augmented Generation (RAG) to analyze game data and queue personalized post-match insights, which were delivered via Discord voice channels.
Developed a Python-based solution leveraging Selenium to automate login and lead imports from the client's insurance dashboard. The tool eliminated manual page refreshes, enabling real-time lead acquisition and increasing the agency's share of leads from a shared pool, significantly boosting operational efficiency and contributed to increased sales volume.
Developed a Python-based system to monitor Windows application usage and visualize the data through a web interface built with Next.js. Focused on dynamic data plotting and interactive charting to provide users with clear, actionable insights. Enabled real-time analysis and enhanced data comprehension through visually engaging dashboards.