Aashish Bagmar

I’m an AI and Data Science undergraduate who builds production-grade software, machine learning systems, and AI-powered applications. I enjoy turning models into real products—especially where responsive experiences and reliable backends matter.

As a Flutter Developer (Freelance), I built and deployed a production-grade Android POS application in Flutter for billing, inventory management, and reporting workflows across a team of 5 employees. I implemented real-time Firestore sync with offline support using Hive caching and an offline queue, cutting manual billing time by 80% and keeping operations uninterrupted without network connectivity.

I also work on AI research and applied forecasting. I co-authored a peer-reviewed paper on AI-powered stock market forecasting that combines real-time news intelligence with predictive modeling, and I’ve continued building hybrid approaches that blend time-series and NLP features.

In my projects, I develop end-to-end AI experiences: a real-time voice healthcare assistant using Speech-to-Text and Text-to-Speech with NLP intent classification and risk tiering, plus a Flutter secure family document platform with biometric authentication, audit logging, and real-time sync. I’m motivated by practical engineering—clean APIs with FastAPI/REST, strong data pipelines with frameworks like Pandas/NumPy/Scikit-learn, and secure, scalable deployments.