How do you implement offline AI summarization for meeting transcripts?
Offline meeting summarization combines local speech-to-text with LLM-powered summarization. The pipeline starts with audio capture from meeting room systems or individual devices. Whisper running locally via faster-whisper or whisper.cpp transcribes speech to text with speaker diarization to identify who said what. The transcript is then processed by a local LLM like Llama 3.1 or Mistral which generates structured summaries including key decisions, action items with owners and deadlines, topics discussed, and open questions. The system can produce multiple output formats including executive summaries, detailed minutes, and topic-specific extracts. For recurring meetings, it can track action item completion across sessions. Running entirely offline ensures sensitive strategic discussions, personnel matters, and confidential business planning conversations never leave the organization network.