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Rulebase

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Automated QA for customer support..

QA
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Agent monitoringMonitor every AI interaction and customer outcome.SimulationsTest agents safely before changes go live.Self improvementsTurn failures into prompt, knowledge, and tool fixes.
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AutoQAReview every interaction, not a sample.InsightsFind quality gaps, risks, and customer signals.CoachingTurn QA findings into focused coaching.
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Customer Operations / AutoQA

Automated QA
for customer support.

AutoQA reads every conversation live and scores it against your SOPs. Failures surface the moment they happen and kick off workflows to alert or fix them.

Rulebase dashboard

Trusted by the fastest growing and publicly traded regulated services.

Nasdaq: LSAKLesaka TechnologiesCase study
Case study

It's invisible until a report.

Scores plateau and don't match reality. Critical failures hide in the 95% of conversations you never read and only surface once they've been counted.

01

Scores plateau and don't match reality.

02

110 agents missing phone-ID checks — caught only in a report.

03

Thousands of expression mistakes a month, invisible until they're counted.

How automated support QA works

Bring calls, chats, and tickets into one review process. Score each interaction against your SOPs, inspect the conversation evidence, and use recurring gaps to guide coaching.

Ashlynn Kenter02:01

Then I got hit with a fee for a failed transaction I didn’t even complete.

01:57

No warning, no explanation.

01:50

I tried to withdraw my money, it got blocked

01:47
Analyzing interactions

01

Reads every conversation

Calls, chats and tickets, the moment they happen, 100%, not a sample.

02

Scores against your SOPs

Every interaction graded against the standards your team is meant to follow.

03

Flags the moment it occurs

Rude tone, escalation language, legal threats and SOP gaps — surfaced as they happen.

What it reads, derives,
and does with it.

What it reads

100% of conversations, in real time — not a sample.

Calls
Tickets
Chats

What it derives

The signals it builds from that data, continuously.

SOP adherence
Tone
Escalation / legal threats
Per-agent error patterns

What it does with it

The signals it builds from that data, continuously.

Flags the issue
Structured score
Per-agent patterns

Common questions

What is automated customer support QA?

Automated customer support quality assurance reviews calls, chats, and tickets against a team’s standards. Rulebase AutoQA scores interactions against SOPs and surfaces quality gaps, escalation signals, and recurring agent patterns for review and coaching.

How should teams use automated QA scores?

Use scores to prioritize investigation, then review the underlying conversation and the criterion that triggered the finding. Calibrate judgments against examples your reviewers agree on, and turn repeated gaps into coaching or process changes. A score is a starting point for review, not a substitute for evidence.

Turn conversation reviews into better support

How Kuda expanded QA coverage →

Read how Kuda moved from reviewing a small sample to covering 98% of its support conversations.

Build coaching from QA findings →

Use patterns in agent conversations to focus coaching on the standards that need attention.

Oremeyi Adeola Okah

“Rulebase is AI for customer ops at fintechs. It watches every interaction, flags risk in real time, and works the follow-up.”

Oremeyi Adeola Okah

Chief Customer Officer at Interswitch

Every customer conversation, covered.

Review calls, chats, and tickets against your standards, then turn quality findings into focused coaching.

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Posted
29 Oct, 2026
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