B2CCustomer experience agent for QA managers
AutoQA
Score every rep on every conversation.
AutoQA scores every ticket, chat and call on the rubric you write, and checks every answer against your knowledge base. Each rep, and your AI agent, gets a scorecard with their trend and what to coach next, down to the moments that lost a customer or could have saved one.

You score a sample. Customers judge every conversation.

of support agents say most of their conversations are never reviewed for quality.
37% say only 0–10% of their interactions get reviewed.
From every conversation to a scorecard for every rep
Three steps. No sampling, no template rubric, and every score links back to the moment behind it.

Ingest
Every conversation, plus your rubric and help center

Analyze
A score on every conversation, with the moment behind it
| Rep | KB accuracy | Coaching note |
|---|---|---|
| Maya Torres | 97% | Strength: offers a pause before every cancel |
| Priya Nair | 82% | Quote the current delivery policy |
| AI agent | 86% | Update the delivery-date article it quotes |

Act
A scorecard for every rep and your AI agent
120 reps scored · team 84 · AI agent 76. Biggest gap: no save offer before a cancel.
Scorecards updated63 flagged, each with the reason, the quote and a link to the conversation.
List updatedOpen a coaching issue for a team lead in Linear, or in any tool you connect through MCP.
See MCP connections →Questions
What sources can it use?
Do I have to use a template rubric?
How does it use our knowledge base?
Where do the results go?
How do I know a score is right?
Coach every rep from every conversation.
Add your rubric, connect your knowledge base and conversations, and get a scorecard for every rep, with every flagged ticket explained.