Transcript Analysis

Speak AI turns recordings into transcripts and pulls out themes, keywords, and sentiment. When a new recording is processed, a Beam agent reads the analysis, applies a customer-approved rule on which topics matter, and files the tagged summary against the right contact or project. Strong sentiment shifts on a key account trigger an alert to the owner. Transcripts where the analysis looks thin, or sentiment reads as sarcasm the model likely misjudged, are handed to a researcher for a second look, so conclusions drawn from the data have a human check behind them.

Language Translation

Speak AI renders transcripts and text into other languages. On a translation request, the agent takes the source text, applies the approved language set for that team, and stores each translated version alongside the original. The requester is notified with links. Requests for languages outside the sanctioned list, or source text still marked as a rough draft, are held and sent to a coordinator, so unreviewed material is not translated and circulated. This keeps multilingual output consistent while leaving final wording decisions for sensitive content in human hands.

Keyword and Theme Extraction

Across a set of transcripts, Speak AI surfaces recurring keywords and topics. A Beam agent reads these on a schedule, applies an approved rule on which terms flag a trend, and updates a themes record for the account or campaign. A spike in a watched keyword notifies the strategy owner. Noisy results, or terms that could be a false pattern from a small sample, are routed to an analyst instead of being written as fact, keeping the trend log trustworthy rather than cluttered with signals nobody has vetted.