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Sachi J.

Student at Shah And Anchor Kutchhi Engineering College

Mumbai

< 1 year of work experience

L&T Precision Engineering and Systems
Dec 20252 mosJan 2026

Mumbai, Maharashtra, India

Engineered MeetSync Pro, an edge AI-powered Meeting Minutes platform using Raspberry Pi for audio capture and Flask microservices backend. Built end-to-end pipeline achieving transcription accuracy and 2.8s real-time latency with Whisper STT and NLP summarization. Key Achievements: Designed hybrid architecture: Pi → WebSocket → Flask APIs → Database Implemented Phase 2 automated MoM generation (summaries, action items via NER) Developed responsive HTML5/JS dashboard with live SocketIO updates Resolved audio buffer overflow, Streamlit-Flask sync issues for zero data loss Optimized for 4+ hour sessions on resource-constrained hardware Tech Stack: Flask, Raspberry Pi IoT, Whisper AI, Transformers, SocketIO, Vanilla JS Impact: Reduced meeting documentation time by 80%, validated through 5 internal sessions (NPS 8.2). Production-ready MVP positioned for enterprise scaling with speaker diarization.

Education

Shah and Anchor Kutchhi Engineering College

Bachelor of Technology - BTech, Electronics and computer science

Shah and Anchor Kutchhi Engineering College

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Sachi J. on Tal

Headline

Student at Shah And Anchor Kutchhi Engineering College

Location

Mumbai

Work experience

AI Intern at L&T Precision Engineering and Systems, Dec 2025 - Jan 2026 · 2 mos, Mumbai, Maharashtra, India, Engineered MeetSync Pro, an edge AI-powered Meeting Minutes platform using Raspberry Pi for audio capture and Flask microservices backend. Built end-to-end pipeline achieving transcription accuracy and 2.8s real-time latency with Whisper STT and NLP summarization. Key Achievements: Designed hybrid architecture: Pi → WebSocket → Flask APIs → Database Implemented Phase 2 automated MoM generation (summaries, action items via NER) Developed responsive HTML5/JS dashboard with live SocketIO updates Resolved audio buffer overflow, Streamlit-Flask sync issues for zero data loss Optimized for 4+ hour sessions on resource-constrained hardware Tech Stack: Flask, Raspberry Pi IoT, Whisper AI, Transformers, SocketIO, Vanilla JS Impact: Reduced meeting documentation time by 80%, validated through 5 internal sessions (NPS 8.2). Production-ready MVP positioned for enterprise scaling with speaker diarization.

Education

Bachelor of Technology - BTech, Electronics and computer science, Shah and Anchor Kutchhi Engineering College

Sachi J. - AI Intern in Mumbai | Tal