A collection of personal projects.
Connect with me on LinkedIn.
An innovative AI-driven customer support engine that provides real-time assistance. The system includes two specialized AI agents: one handles frequently asked questions, while the other tracks order status and product details. It empowers users to effortlessly query about their orders, cancel requests, contact support, and more, offering a seamless pre- and post-purchase experience.
A groundbreaking AI solution that tackles financial market complexity through three collaborative agents. By combining real-time web research, market data analysis, and strategic coordination, the system transforms overwhelming financial information into clear, actionable insights. It eliminates hours of manual research, helping investors make faster, data-driven decisions by automatically synthesizing market trends and news impacts.
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A bot designed to handle frequently asked questions for e-learning platforms. Using RAG and embedding vector storage, it answers the top 60 user queries, replacing the need for human intervention.
An innovative bot using RAG to extract and summarize important information from news articles. Upload a news URL, ask your questions, and get precise insights without manual effort.
An AI-powered bot capable of analyzing X-ray reports to provide detailed feedback and insights using its extensive knowledge. A transformative tool for the healthcare sector.
A Streamlit-deployed AI project where users can upload documents and interact with them through a question-and-answer interface. A practical real-world use case for document analysis and retrieval.
Upload a YouTube video URL, and this AI tool will extract and summarize key information from the video. It uses advanced embedding and retrieval techniques to deliver concise summaries.
Here, I built a Time series model(ARIMA) to predict Stock Price. Here, I did pre processing , checked for stationarity , Trends , Seasonality .Used some transformation to fit into the model and lastly perfomed PACF and ACF.
Building a multivariate linear regression model from scratch. Conducting exploratory data analysis and feature engineering to build an efficient model to predict house prices.
Here, I built a Decision Tree Classifier model to predict Loan approval using a set of given variables. I used feature engineering and data processing on the data set.
Here, I built a Logistic Regression model to predict Heart Disease using a set of given variables. A pipeline was used for efficient data preprocessing on the test dataset.
Techno India University, Expected Graduation in August 2025