B2BCustomer 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 put an account at risk or left growth on the table.

Paste in your AI agent

Copy this line into ChatGPT, Claude, Gemini or your coding agent. It takes it from there.

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The problem

You score a sample. Customers judge every conversation.

81%

of support agents say most of their conversations are never reviewed for quality.

37% say only 0–10% of their interactions get reviewed.

Source: Solidroad, State of CX 2026 (500 full-time support agents, June 2026)
How it works

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

Your rubric
Knowledge base
Help desk
Calls
AI agent
Anything else
Rippit

Analyze

A score on every conversation, with the moment behind it

One row per repAutoQA adding fields…
RepKB accuracyCoaching note
Maya Torres98%Strength: gives a time for every update
Priya Nair84%Use the current SSO article, not the old one
AI agent88%Retire the export article it keeps linking
63 conversations flagged this week · 18 at key accounts

Act

A scorecard for every rep and your AI agent

Rep scorecards + QA dashboardNotion or Google Drive

42 reps scored · team 88 · AI agent 79. Biggest gap: CSM handoffs on upset key accounts.

Scorecards updated
Flagged tickets

63 flagged, each with the reason, the quote and a link to the conversation.

List updated
+ Any connected MCP

Open a coaching issue for a team lead in Linear, or in any tool you connect through MCP.

See MCP connections →
FAQ

Questions

What sources can it use?

Help desk tickets and chats from tools like Zendesk or Intercom, calls from Gong or Fireflies, your AI agent’s conversations from Decagon, Ada or Sierra, and Slack channels you invite Rippit to. Your rubric, help articles and internal policies come in by CSV or the Ingest API. See integrations →

Do I have to use a template rubric?

No. You write the criteria, the weights and what good looks like for each one, so scores reflect how your business works, not a generic checklist. The same rubric applies to your reps and your AI agent, and you can change it any time.

How does it use our knowledge base?

It checks every answer against your articles and internal policies. A rep who quotes an old setup step or links the wrong article gets flagged, with the article that has the right answer, and repeat misses show up on that rep's scorecard.

Where do the results go?

Rep scorecards, flagged tickets and the coaching playbook go to Notion or Google Drive, and a weekly summary goes to Slack or email. Anything else, like a coaching task, can go to Linear or any tool you connect through MCP. It runs every morning by default, and you can change it to hourly or weekly any time. See MCP connections →

How do I know a score is right?

Every score comes with the reason and the quote behind it, plus a link to the conversation, so your team can check it before it goes into coaching. Run it on a sample first and compare it with your own reviewers before you turn it on for everything.

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.

Paste in your AI agent

Copy this line into ChatGPT, Claude, Gemini or your coding agent. It takes it from there.

Set me up with rippit.com
Try Rippit free
or request demo