Draft PRDs grounded in customer evidence
For when you need more than 'customers want this' in your spec.
How teams use Enterpret today
Situation
A PM was writing a PRD for a new collaboration feature and needed to prove customer demand beyond anecdotes.
Action — asked Enterpret AI
Pull all customer evidence related to collaboration or team features. Include total account count, ARR breakdown by segment, and the top 5 verbatim quotes.
Impact
PRD went from "customers want collaboration" to "47 accounts ($2.1M ARR) across 3 segments have raised this, with 78% expressing high frustration."
Situation
A product team needed to understand what specific problems customers expected a feature to solve — not just that they wanted it.
Action — prompted Claude with Enterpret MCP connector
What specific use cases or workflows do customers describe when requesting [feature]? Show the most detailed descriptions.
Impact
Discovered 3 distinct use cases behind a single feature request. The PRD addressed all 3 instead of building for the assumed primary one.
Situation
The PRD was written with customer evidence, but the PM needed the specific customer themes tracked alongside the implementation tickets.
Action — linked PRD evidence to Jira or Linear work items
Linked the feedback themes cited in the PRD to the corresponding Jira or Linear implementation tickets. Each ticket received the customer demand data — account count, quotes, and sentiment — so engineers could reference it during development.
Impact
During code review, engineers could see the customer evidence attached to the ticket they were working on. The "why are we building this?" question was answered before it was asked.
