Contact Center QA & Real-Time Sentiment
See how 100% automated QA, real-time dashboards, and sentiment tracking help AI agents improve, and why how a call ends matters most.
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About this session
In this short from a contact centre summit panel, Anubhav Mohanty of Orvera AI explains how 100% automated QA keeps AI agents improving after launch. Every call is scored, and the results feed a real-time dashboard of outcomes and top areas of opportunity, which then go back to developers to tune the agent, because no AI agent is perfect on day one.
He also explains why sentiment should be tracked in real time. A call can start very differently from how it ends, and from a customer experience standpoint what matters is the ending; turning an irritated, frustrated caller into a satisfied one is a major win. The clip is designed for contact center and QA leaders.
Key takeaways
What comes out of it
100% auto-QA. Every call is scored, not a sample.
Real-time dashboards. Teams monitor outcomes and top opportunities daily.
A feedback loop. QA findings go back to developers to tune the agent.
Not perfect on day one. Continuous improvement is part of the plan.
The ending matters most. Moving a caller from frustrated to satisfied is the real win.
TranscriptRead the full session
Anubhav Mohanty 00:00:00.00 We do 100% auto-QA and then do a dashboard out of that QA so that you are also on a daily basis, real-time monitoring what the outcomes are, what your top areas of opportunities are. And that goes back to a feedback mechanism to the developers to kind of tweak the AI agent. So because it cannot be perfect on day one. And then on the sentiment side of it, we also, it should be a real-time sentiment tracking. The start of the call can be different and the end of the call is different. But from a customer experience standpoint, what matters is how did the call end?
Anubhav Mohanty 00:00:31.40 So if an AI is able to get the sentiment from irritated and frustrated to satisfied, I think that's a huge win.
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