
September 2023 Releases
Building an AI agent is just the first step. The biggest challenge is getting it to perform at scale.
Your first version will need refinement, and once real conversations begin, it becomes critical to pinpoint which calls are driving poor outcomes and extract actionable patterns so you can adjust your prompt, voice settings, or knowledge base.
The difficulty lies in managing thousands of conversations with no efficient way to review them. It's hard to know where to start, which recordings will be most useful, or how to surface specific issues that can be addressed. And since you can’t listen to every conversation, you risk missing the insights that could drive real impact.
Regal IQ closes this gap. Our new Conversation Insights Dashboard gives you a clear view into the key themes emerging across your AI agent calls and how those conversations are performing.
You can drill into subtopics to see which are hitting your benchmarks (and which aren't), and review a focused set of calls that surface the most important areas for improvement. With no setup, Regal IQ surfaces gaps in your knowledge base, recurring objections, and underperforming dialogue flows so you can make tailored, data-driven updates that strengthen your agent over time.
Regal IQ uses LLMs and unsupervised clustering to extract the most relevant moments from calls and group them into high-level topics. This gives you a fast, objective view of what’s really driving your AI agent interactions, so you can focus your efforts on the patterns that actually impact outcomes.
Instead of sampling calls at random or guessing what to look for, the topic classification widgets help you quickly answer:
In the dashboard above, “Business Use Case Exploration” emerges as the top reason customers are engaging with the agent.
You might have expected pricing or product setup to dominate, but instead the data reveals something less obvious—customers are still trying to understand how the product fits their needs.
With this insight, you could prioritize adding industry-specific use cases to your knowledge base or refining your prompt to better handle discovery conversations, rather than optimizing objection handling or support flows.
Regal IQ updates daily with new transcript data, giving you visibility not just into the most common conversation topics, but into which ones are trending upward. This helps you stay ahead of potential issues by spotting emerging topics where your AI agent may lack coverage or deliver poor outcomes, so you can take action before they become bigger problems.
Once you’ve identified the most impactful topics, Regal IQ lets you drill deeper to see which subtopics are surfacing most and how they’re performing.
Metrics like talk time and contact sentiment help you quickly pinpoint where your agent is falling short. Plus, Regal IQ dashboards are fully customizable so you can track the metrics that matter most for your use case, whether that’s transfer rate, appointment bookings, resolution time, or something else entirely.
The above image shows real data from our sales agent Reggie. We can see that in conversations where pricing is mentioned, prospects are specifically interested in Regal's pricing structure and the cost savings associated with using an AI agent, and these conversations tend to take longer than average. If the higher duration is due to verbose agent answers or customer confusion, refining the Knowledge Base with clearer, more concise pricing content could speed up these interactions and improve contact sentiment.
In an inusrance context, within the broader topic of “Claims Process,” you might see that “Required Documentation” is driving unusually long call durations and poor sentiment.
That signal helps you focus your investigation, not just on the topic itself, but on the specific aspect of the conversation that’s leading to friction.
This level of visibility enables you to:
Every subtopic includes a curated set of representative calls, so you can quickly explore real examples and hear how your agent is handling specific moments. Instead of sorting through random transcripts or listening blindly, you go straight to the conversations that matter.
In the table above, we’re looking at transcripts for a home services company, filtered to the “Pricing and Cost Inquiries” topic. Regal IQ instantly surfaces every moment where prospects discussed pricing — from comments like “the quote of $2,000 for the installation just seems too expensive” to questions such as “how do you charge for the fence installation?”.
With these moments in one place, it’s easy to spot patterns: perhaps the agent isn’t breaking down costs clearly, isn’t tailoring answers to context, or is missing opportunities to highlight savings. From there, you can update KB content with exact price breakdowns, refine prompts to guide the conversation more efficiently, or add pre-approved responses for common objections
Recording-level precision enables you to:
Most AI agents don’t fail because of model performance—they fail because teams don’t have the tools to understand where things are going wrong or how to fix them. Regal IQ gives you that missing visibility.
With the new Conversation Insights Dashboard,you can easily spot failure points, prioritize the right updates, and measure their impact over time. Whether it’s surfacing knowledge gaps, flagging objection patterns, or identifying broken flows, Regal IQ turns raw transcript data into targeted actions.
Paired with Regal’s RAG-powered Knowledge Base, you get a complete feedback loop, from insight to fix to measurable improvement, all in one system.
Ready to see Regal in action?
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