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Schedule Interview NowWorking at Softaims has been an experience that continues to shape my perspective on what it means to build quality software. I’ve learned that technology alone doesn’t solve problems—understanding people, processes, and context is what truly drives innovation. Every project begins with a question: what value are we creating, and how can we make it lasting? This mindset has helped me develop systems that are both adaptable and reliable, designed to evolve as business needs change. I take a thoughtful approach to problem-solving. Instead of rushing toward quick fixes, I prioritize clarity, sustainability, and collaboration. Every decision in development carries long-term implications, and I strive to make those decisions with care and intention. This philosophy allows me to contribute to projects that are not only functional, but also aligned with the values and goals of the people who use them. Softaims has also given me the opportunity to work with diverse teams and clients, exposing me to different perspectives and problem domains. I’ve come to appreciate the balance between technical excellence and human-centered design. What drives me most is seeing our solutions empower businesses and individuals to operate more efficiently, make better decisions, and achieve meaningful outcomes. Every challenge here is a chance to learn something new—about technology, teamwork, or the way people interact with digital systems. As I continue to grow with Softaims, my focus remains on delivering solutions that are innovative, responsible, and enduring.
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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