Customer Support

Automating quality monitoring across AI and human support

AI reviews support conversations and calls, scores them against custom quality criteria like accuracy, tone, policy adherence, and coaching frameworks, and helps teams improve both AI-agent and human-agent performance at scale.

Why the human is still essential here

Managers and QA leads still define what good support looks like, interpret the scores, coach teammates, and decide corrective actions. AI expands coverage, but quality standards and coaching stay human-led.

How people use this

Automated ticket QA reviews

AI scores every support interaction against quality standards and flags risky or low-quality conversations for manager follow-up.

Zendesk QA

Custom scorecards at scale

AI applies team-specific QA rubrics across chat, email, and tickets so support leaders can review performance trends without manual sampling.

MaestroQA

Semantic quality monitoring

AI evaluates conversations for compliance, empathy, and resolution quality while surfacing coaching opportunities for both agents and bots.

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Related Prompts (1)

Latest community stories (2)

Tool Recommendation
LinkedIn

Riding along on customer calls to coach my CSMs was one of the most well-intentioned things I did as a leader.

Riding along on customer calls to coach my CSMs was one of the most well-intentioned things I did as a leader.

But if I’m being honest it was actually a disaster.


Here’s the reality, scheduling was a nightmare, my presence made customers question the CSMs credibility and authority, and I could tell my CSMs were nervous all day, not just during the call.


And when I tried to give helpful feedback after the call was over, it almost always landed as criticism. Even if that wasn’t my intention.


I wanted to develop my team, but what I actually did was create friction for my customers, my CSMs, and myself.


When call recordings came along they felt like the answer, and they were, in theory.


But in practice, all I had were folders full of calls and zero time to actually listen to them. Something always got prioritized over it. That's on me. But it was the reality for a lot of us.


The tools just weren't there yet.


That's changed.


I've been digging into Aircall's AI Assist Pro and honestly, it's the thing I wish I'd had when I was still managing a team.


Here's what actually caught my attention:


1️⃣ It surfaces call frameworks automatically. I'm a MEDPPICC leader, but you can build out whatever framework your team uses. It ensures your CSMs are hitting the right moments in every conversation, not just the ones they remember.


2️⃣ It brings competitive intel and product tips up in real time. Your CSM doesn't have to fumble through an objection, they have the answer right there. This is huge with product innovation moving so fast.


3️⃣ Every call gets scored automatically based on the criteria that matter to you. No more listening to 47 recordings to find the three that need attention. This also removes any bias and ensures everyone is being scored across the same criteria, the same way.


4️⃣ It spots trends across all your calls. So instead of guessing what customers are asking for, you actually know and have the data and insights to back it up.


I'm not running a CS team right now. But one of my clients is using this, and watching it in action made me a little jealous of the resources CS leaders have today.


The tools have come a long way since 2012.


Are you still riding along on calls or listening to recordings? Would you try this?


If you’re interested in checking this out, you can read more about the AI Assist Pro and their other AI features that are worth exploring.

https://bit.ly/4fRfow3


In partnership with Aircall.

KF
Kristi FaltorussoCustomer Success Consultant
Jun 2, 2026
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IntercomCustomer support software company
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