Manual QA is broken—and AI is here to fix it.
In our recent webinar, Break Free from Manual Call Reviews, we explored how AI and LLM-powered insights are transforming quality assurance in contact centers. From reducing hours of manual work to boosting coaching outcomes and customer satisfaction, the shift to automation is already happening.
Missed the live session? Watch the full webinar on demand here →
Before you do, here are the top takeaways to bring you up to speed and show you what AI can do for contact centers.
1. Manual QA Leaves 95% of Conversations Untouched
Legacy call review processes are slow, rigid, and limited. Only 1–5% of calls get reviewed—leaving the majority of customer feedback, agent behavior, and service issues completely hidden.
2. With LLMs, You Can Just Ask—and Get Instant Answers
Large Language Models (LLMs) change the game. Instead of relying on static keyword tagging, business users can simply ask plain-English questions like:
- “Why are customers calling this week?”
- “Was the customer’s issue resolved?”
- “Did the agent acknowledge the complaint?”
The system returns structured answers, complete with evidence, reasoning, and timestamps—no analyst required.
3. Conversation Insights Agent Is Already Delivering
The demo showcased how Conversation Insights Agent is being used today to:
- Automatically score agent performance
- Build dynamic QA scorecards from plain-language prompts
- Spot coaching gaps and emerging call patterns
- Empower business users to self-serve insights
- Visualize performance trends and sentiment shifts across calls
A big insurance company saw measurable improvement in first contact resolution and customer retention just weeks after adopting the system.
4. Visual Coaching Tools Bring the “Why” to the Surface
Agent performance isn’t just scored—it’s explained.
Supervisors can see exactly where agents are underperforming, which behaviors are working, and how those correlate to outcomes like AHT, CSAT, and resolution rate. They can also trace coaching results over time using dashboards that track sentiment, behavior, and customer effort.
5. Ask Your Data: The Next Step in Agentic AI
Uniphore previewed its upcoming agentic system—Ask Your Data—which doesn’t just surface insights, but executes next steps using your conversation data.
Picture this:
- The system identifies a trending issue (e.g. wildfire-related calls)
- It flags low agent performance on that issue
- Recommends updated scripting
- Pushes changes into the real-time agent guidance tool
- Tracks impact over the next 7 days
This loop—from insight to action to impact—is fully closed, thanks to AI that understands context and takes initiative.
6. Accuracy, Trust, and Security Are Built In
Uniphore’s AI isn’t a plug-and-play model. It’s trained on billions of minutes of enterprise conversation data, fine-tuned continuously, and evaluated using real customer feedback.
Features like RLAIF (Reinforcement Learning with AI and Human Feedback) ensure reliability. Privacy, compliance, and customer data protection are foundational—not an afterthought.
Watch the Webinar Replay
If you’re ready to see how GenAI conversation intelligence is changing the QA game—and how your team can get there—watch the full replay.
Want a deeper look?
