moomena asad

I’m an AI student with hands-on experience building LLM-powered applications, RAG pipelines, and NLP systems through internships and research. I focus on designing and implementing end-to-end AI solutions—from model development to API integration and full-stack deployment workflows.

In my AI / Machine Learning internship at IT Solera, I developed machine learning models for data analysis and predictive tasks using Python libraries like Pandas, NumPy, and Scikit-learn. I handled the full modeling cycle—data preprocessing, feature engineering, training, and evaluation—and contributed to AI-based reporting for business decision support.

As a Chatbot Development intern at DevShield IT, I designed NLP-based conversational AI workflows using prompt engineering and API integrations. I built and deployed end-to-end chatbot lifecycles (design, testing, debugging, deployment) and integrated third-party APIs to improve conversational intelligence and automation.

My projects reflect how I like to work: ClauseWise uses RAG with embeddings for contract Q&A, clause analysis, risk scoring, and explanation generation, with a FastAPI backend and a React UI. I also built an agentic internship application system using LLM-based reasoning plus the Gmail API, including human-in-the-loop safeguards. I’m drawn to efficient ML systems, document intelligence, and agent-based AI that can ship reliably.