transcript-analyzer

Meeting transcript analysis uses AI to automatically extract decisions, actions, opinions, questions, and domain terms from your text. It processes long business meetings and project reviews via chunked AI analysis to produce structured summaries and a glossary.

Yes, you can integrate an existing glossary when extracting domain terms from transcripts. The analysis proposes new terms with inferred definitions, compares them against your current glossary, and provides confidence scores to evaluate the newly identified vocabulary.

Yes, the transcript analyzer works with long cross-functional meeting reviews by applying chunked AI processing. This method breaks down lengthy discussions to systematically extract decisions, actions, opinions, and domain terms without losing context.

The best way to generate a structured summary from project review transcripts is to use an AI extraction tool that outputs a structured Markdown document. This document includes categorized extractions, glossary terms, and metadata like extraction counts for stakeholder sharing.

Yes, you need an OpenAI dependency to analyze meeting transcripts with this tool. The AI processing relies on OpenAI models to handle the chunked transcript analysis, categorize extractions, and infer definitions for new domain terms.