{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/16bbb05b07b641509eb2a3a2d68f45a0\" frameborder=\"0\" width=\"1920\" height=\"1440\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1440,"width":1920,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1440,"thumbnail_width":1920,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/16bbb05b07b641509eb2a3a2d68f45a0-49a2e8eb34f4db76.gif","duration":127.21,"title":"Offline Live Event Voice Capture Architecture","description":"This Loom describes the architecture for a secure offline-first live event capture system that records counselor conversations and extracts insights. The reporters submit via mobile phones while admins manage from an admin dashboard, and the AI provides insights, anomaly detection, and a Compositional Voice Capture module for live events. During live events, counsellors capture converts decisions through conversations and the system records the audio, then transcribes it using NLP with RECX to extract fields and send results to the server in real time even without internet, storing offline to sync later. It also discusses using plot code to support architectural decisions, implementation, debugging, memory tuning when servers begin to OOM, and Docker Compose configuration management, concluding with secure, scalable, resilient, complete results."}