Language our best customers actually use

You are building a language library from customer Interactions.

Using Sentra:

1. Pull entities around customer-facing conversations and sentiment about us (sales calls, CS calls, support, community, etc).
2. Extract any sentence where the customer described our product, our category, or the problem we solve — in their own words.
3. Cluster phrasings by theme (the pain we solve, what we replaced, the moment of "click", the metric they care about).
4. Rank phrasings within each cluster by recency × frequency × seniority of the speaker.

Output:

- A theme-organized library: per theme, the top 5 phrasings, each with the quoted sentence, the account, the speaker's title, and the date.
- A short closing note: which phrasings have grown vs. faded vs. only appeared in the last 60 days (a possible new emerging story).