Learn how to build low-latency real-time audio processing pipelines for meeting bots using Python. Covers audio streaming, VAD, speech-to-text, sentiment analysis, and the MeetStream API for capturing audio from Zoom, Google Meet, and Teams.

WebRTC vs RTMP for live meeting bot streaming — a developer comparison of latency, scalability, browser support, and platform compatibility. Learn which streaming protocol fits your meeting bot architecture for Zoom, Google Meet, and Microsoft Teams integrations.

Apply zero-shot topic classification to meeting transcripts using transformer models. Learn how to automatically categorize meetings by topic — sales, support, engineering, strategy — without labeled training data, using Hugging Face pipelines and the MeetStream API.

How to automatically extract action items and tasks from meeting transcripts using NLP. Covers intent classification, task extraction pipelines, prompt engineering for LLMs, and integration patterns for routing action items to project management tools via the MeetStream API.

Implement custom Named Entity Recognition in your AI meeting bot to extract names, dates, organizations, and domain-specific entities from transcripts. Covers NER techniques, model training, integration with MeetStream, and practical code examples for meeting intelligence.

Deep dive into speaker diarization for meeting bots — techniques for identifying who said what in multi-speaker conversations. Covers clustering algorithms, neural approaches, real-time vs batch processing, and how to integrate speaker identification via the MeetStream API.

How to write comprehensive unit and integration tests for AI meeting bot workflows. Covers testing strategies for real-time event handling, webhook processing, transcription pipelines, and platform integrations with practical code examples and CI/CD patterns.