I am a Full Stack AI Systems Engineer specializing in designing and building intelligent software systems that combine modern web development, artificial intelligence, workflow automation, and scalable cloud infrastructure.
I build production-ready AI applications that transform how organizations access information, automate operations, and make data-driven decisions. My work spans full-stack development, Retrieval-Augmented Generation (RAG), AI agents, backend APIs, workflow automation, and cloud deployment.
Document Copilot is a full-stack AI application built to help analysts search and retrieve insights from SEC filings using natural language. The platform combines semantic search with Retrieval-Augmented Generation (RAG) to deliver grounded, citation-backed responses from a curated document corpus.
Investment analysts spent nearly half of their working week manually reviewing lengthy SEC filings before producing research. The process was repetitive, time-consuming, and difficult to scale, reducing the time available for high-value analysis.
Developed a browser-based AI knowledge assistant that enables analysts to:
The application was designed with a strong focus on accuracy and trust, ensuring responses are based only on the uploaded documents and never fabricated beyond the available evidence.
The platform follows a modern full-stack AI architecture: