The Vision
As a Tech Innovator and AI enthusiast pursuing my BCA at MDU Rohtak, I’ve always believed that data should do more than just sit in a database—it should understand us. While my experience in data analytics simulations at Deloitte and Goldman Sachs taught me how to handle large-scale enterprise data, I wanted to apply those rigorous standards to something more human: Mental Well-being.
This led to the creation of MindPulse AI.
The Problem: The Monitoring Gap
Traditional mental health tracking is often manual, subjective, and retrospective. People struggle to accurately label their emotional states in real-time, leading to undetected burnout and stress.
The Solution: Multimodal Fusion
MindPulse AI isn't just a sentiment analyzer. It's an intelligence engine that synchronizes:
Textual Analysis: Understanding context and intent using NLP.
Voice Analytics: Detecting stress through vocal patterns (Web Speech API).
Visual Cues: Analyzing facial micro-expressions for a 360-degree emotional view.
Technical Deep-Dive
Building this required a robust and scalable infrastructure:
The Brain: Integrated Google Gemini AI for complex reasoning and multimodal data fusion.
Frontend Mastery: Developed with React.js and Tailwind CSS, featuring a high-fidelity Claymorphic & Glassmorphic UI to reduce user anxiety.
Data Integrity: Applied statistical data analysis skills to ensure the accuracy of our 30+ mood state mappings.
Why It Matters
This project is a culmination of everything I’ve learned—from software engineering at Goldman Sachs to business visualization at Tata Group. It’s about building technology that doesn't just calculate, but empathizes.
Live Demo: https://mindpulse--ai.web.app/ GitHub: https://github.com/RAHULKHATI369/MindPulse-AI.git
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