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Schedule Interview NowMy journey at Softaims has been defined by curiosity, growth, and collaboration. I’ve always believed that good software is not just built—it’s carefully shaped through understanding, exploration, and iteration. Every project I’ve worked on has taught me something new about how to balance simplicity with depth, and efficiency with creativity. At its core, my work revolves around helping businesses and people achieve more through thoughtful technology. I’ve learned that the most successful projects come from teams that communicate openly and stay adaptable. At Softaims, I’ve had the opportunity to work alongside professionals who challenge assumptions, share knowledge generously, and inspire continuous improvement. I take pride in focusing on the fundamentals—clarity in logic, consistency in design, and empathy in execution. Software is more than a set of features; it’s a reflection of how we think about problems and how we choose to solve them. By maintaining this perspective, I aim to build solutions that are not only effective today but also flexible enough to support the challenges of tomorrow. The culture at Softaims promotes learning as an ongoing process. Every new project feels like a step forward, both personally and professionally. I see each challenge as a chance to refine my skills and contribute to the shared vision of building technology that genuinely improves lives.
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I developed StockSeer-API, a FastAPI-based application for stock price prediction. Using machine learning models like RandomForestRegressor, ExtraTreesRegressor, LinearRegression, KNeighborsRegressor, and LSTM, the API predicts closing stock prices based on historical data fetched from Yahoo Finance. It supports data preprocessing, model training, and future price forecasting. StockSeer-API offers an interactive interface via FastAPI documentation for seamless integration. Users can train custom models and make predictions, with clear disclaimers about financial decision-making risks.
I created BestRAG, a Python library that efficiently stores and retrieves embeddings using hybrid Retrieval-Augmented Generation (RAG). By integrating dense, sparse, and late interaction embeddings, it ensures robust search performance for large datasets. Key features include PDF integration for seamless embedding storage and retrieval. BestRAG gained 1.3K+ downloads within its first month, showcasing its impact and usability. Developers have praised its simplicity, API integration, and performance, making it a valuable tool for document and data management solutions.
Developed QueryPLS, a cutting-edge web application that leverages advanced AI and Large Language Models (LLMs) to seamlessly convert natural language queries into accurate SQL statements. Recognized by LangChain for its innovation, QueryPLS ensures high accuracy, efficiency, and user-friendly interaction
MediSync is a comprehensive hospital management solution designed to address the challenges of efficient patient record management, doctor scheduling, and appointment coordination. Leveraging Django, HTML, CSS, JavaScript, and REST API, I developed this robust system to streamline healthcare facility operations. MediSync offers a user-friendly interface that centralizes patient and doctor data, automates appointment scheduling, and ensures secure data management.
Bachelor's degree in Software Engineering
2021-01-01-2025-01-01