About This Architecture

Meeting Intelligence System Architecture orchestrates real-time audio capture, automatic speech recognition, and NLP processing to extract actionable insights from business meetings. Audio flows from Meeting Audio Input through Audio Capture Module to ASR, then through NLP Processing (Tokenization, Lemmatization) into an Intelligence Layer that runs Summarization, Named Entity Recognition, and Action Item Detection models. Processed intelligence is persisted in Secure Cloud Storage and surfaced via Dashboard Interface, enabling teams to search transcripts, track decisions, and automate follow-ups without manual note-taking. This multi-cloud architecture demonstrates how to build scalable meeting analytics that reduce administrative overhead and improve meeting accountability. Fork this diagram on Diagrams.so to customize for your cloud provider, add authentication layers, or integrate with calendar and task management systems.

People also ask

How do you build a scalable meeting intelligence system that captures audio, transcribes it, extracts insights, and surfaces them in a dashboard?

This diagram shows a seven-stage pipeline: Meeting Audio Input → Audio Capture Module → ASR → NLP Processing (Tokenization, Lemmatization) → Intelligence Layer (Summarization, NER, Action Item Detection) → Secure Cloud Storage → Dashboard Interface. This architecture enables teams to automatically transcribe meetings, extract entities and action items, and access insights without manual note-takin