
September 2023 Releases
New LLMs are emerging faster than ever, each with unique strengths in reasoning, speed, and cost. But keeping pace with that evolution can be time-consuming and technically complex, and staying current often means sacrificing focus or stability.
Regal now supports 10 new models across OpenAI, Anthropic, and Google—including GPT-5, Claude 4.0, and Gemini 2.5—making it easy to continuously experiment with the latest advancements and identify the best model for your use case. With Regal’s native testing and A/B experimentation framework, you can safely compare models, measure impact in real time, and stay ahead as the LLM landscape evolves.
Explore how the latest LLMs can help you:
Track how contacts respond to AI interactions with the new Receptiveness to AI metric. This agent-specific, real-time stat displays the percentage of AI conversations without a no_ai function invocation—customizable to your definition of disengagement, such as when a contact prefers a human agent or finds the AI agent unhelpful. Use this metric to gauge how effectively an agent engages contacts after a launch or update, or to measure contact receptiveness to AI as a proxy for containment rate or overall conversational quality.
Manage high-volume outbound campaigns more efficiently with Dynamic Campaign Priority. As AI Agents unlock unlimited dialing concurrency and capacity, Regal enables you to handle more call attempts without the added complexity. All call attempts can now be managed with a single campaign, with Regal automatically setting and tracking priority so the first call is always attempted before the hundredth. Use the new campaign_call_attempt field on the call.completed event to reference a call’s attempt number in Journeys and Reporting for precise pacing, routing, and performance insights.
For early access to Dynamic Campaign Priority, reach out to your Customer Success Manager.
Create more lifelike simulations by assigning mock values to contact variables such as age, state, or budget. AI Agents can now reference these values during end-to-end simulated conversations, adjusting tone, content, and decisions just as they would in production. With predefined test values, you can confidently test complex, persona-based scenarios at scale and ensure every path performs as intended before launch.
Gain deeper visibility into AI Agent behavior by viewing action invocations directly alongside call transcripts in Conversational Intelligence. See how each action aligns with live dialogue to quickly diagnose where logic may break down—like a delayed function call or an unexpected response— and expand payload details to validate timing and data flow for smoother execution end-to-end.
Access your Call Restrictions settings directly in Regal to review daily available hours, holidays, state-of-emergency rules, and state-specific call attempt limits. With this shared, in-app view, your teams can stay aligned on calling policies and quickly identify when updates are needed to maintain compliance and optimize outbound coverage.
Build complex pathing for advanced agents using the Multi-State Agent Builder. Agents will transition seamlessly between states and branch the conversation based on information available before and gathered during a call.
Embed AI Agents directly into your apps and websites with Regal’s WebRTC SDK, enabling contacts to start conversations seamlessly, without ever dialing a phone number.
Make changes to your call restriction settings in the Regal app to manage daily contactable hours, holidays, state-of-emergency rules, and call attempt limits with full flexibility and control.
Ready to see Regal in action?
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