C-36 tanishka waghmare

Full-Stack Developer

Dr. D. Y. Patil Institute of Technology.full_time, internship

Open to roles

CommunicationGITAgile/ScrumProblem Solving

FlytBase AI Inbound BDR Assistant

Built an AI-powered inbound BDR assistant for the FlytBase hiring hackathon that automates the workflow of a sales development representative. The system analyzes inbound lead emails through an 8-agent AI pipeline: - Email parsing and lead extraction - MEDDPICC-based qualification - Company research and account intelligence - Buying signal detection - Case study matching - Go-to-market recommendation - Personalized outreach generation - AE handoff summary The backend is built using FastAPI and integrates AI agents to transform raw inbound emails into actionable sales insights for faster lead qualification and routing. The solution helps BDRs reduce manual research effort and make data-driven decisions for enterprise drone software sales.

2 media files · github.comView

Queue Cure '26 — Real-Time Patient Queue System

Clinics rely on paper tokens and manual announcements — patients have no visibility into wait times and receptionists have no way to manage the queue digitally. This causes confusion, missed calls, and long perceived waits even when the actual queue is short. Process I broke the problem into three parts: where state lives, how changes sync instantly across screens, and how wait time is computed honestly. I chose a single server-side state object so there's one source of truth. Socket.IO broadcasts a full snapshot to all connected clients on every change — no polling, no refresh. Wait time is computed dynamically using time elapsed since the current patient was called, not a hardcoded estimate. Results Live sync achieved in under 50ms across receptionist and waiting room screens. Wait time decays in real time as consultations progress. Receptionist screen handles empty queue, duplicate calls, and XSS input safely. Deployed on Railway with zero-downtime auto-deploy from GitHub. Reflection Add Redis for persistent state so the queue survives server restarts. Support multiple doctors with parallel token streams. Send WhatsApp alerts when a patient is 2 spots away.

3 media files · queue-cure-26-production-baa3.up.railway.appView

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