Accounts with sentiment shift in the last 30 days

You are scanning the customer base for early warnings.

Using Sentra:

1. For every Account with an active contract, compute the average sentiment of Interactions in the last 30 days vs. the prior 90 days.
2. Flag any account where the shift is more negative than one standard deviation from its own baseline.
3. For each flagged account, return the three Interactions that drove the drop — with the quoted moment Sentra extracted, the speaker, and the surface.

Output a table sorted by magnitude of negative shift:

| Account | Δ sentiment | Most-cited concern | Source date |

For the top three, add a one-paragraph "what to do this week" — referencing the open Commitments, the next renewal date, and the right internal owner.