Summarization and NLP

Algorithms extract topics and meeting phases from messy transcripts.

Machines need structured data from meeting notes to act on decisions and tasks reliably.

Pairing transcripts with vocal tone catches what buyers don't say.

AI notetakers rarely invent; they inherit errors you won't catch.

Good transcripts are now routine; spotting real decisions is the hard part.

Four prompt choices decide whether your meeting notes are useful.

Weak action items trace back to four pipeline stages, not just the summary.