
September 2023 Releases
In 2026, we're focused on making every interaction with your AI agent feel more human, and speeding up the agent development process so you can drive results faster.
We kicked off the year by advancing the reach and contextual intelligence of AI agent conversations: context retrieval with IVR GET requests means your agent knows your customer from the first second of the call, support for 11 new languages expands your agent's reach, and new LLM models make even the most complex conversations feel more natural.
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Regal’s IVR can now send GET requests to retrieve customer data before the call connects, so your AI agent starts every conversation fully informed.
For example, a request to your policy system can instantly return coverage details, claim history, and account status before the agent utters their first speech. That context powers smarter routing, more personalized conversations, and seamless handoffs that feel tailored from the very first second.
When an agent greets a customer with relevant information already in hand without having to say “one moment while I pull up your information”, issues are resolved faster, interactions feel more thoughtful, and operations run more efficiently – driving quicker resolutions and deeper customer trust.
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Serve more of your customers with AI agents that now converse in Bulgarian, Danish, Finnish, Greek, Hungarian, Indonesian, Malay, Norwegian, Romanian, Slovak, and Swedish.
Your AI agents can now leverage GPT-5.2 and Gemini 3 Flash. GPT-5.2 excels at complex, long-running conversations requiring deep reasoning and precise instructions, such as troubleshooting, advanced support, or sales discovery. Gemini 3 Flash handles fast, high-volume interactions like lead capture, routing, and real-time conversations with strong multimodal understanding and efficient agentic workflows.
Each model has its relative strengths and weaknesses. We recommend using Test Cases & Simulations to stress test new models before switching, as you may need to tweak your prompt.
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The new Authenticate Contact action enables AI agents to securely handle calls that require sensitive access. During live conversations, customer-provided information is verified in real time against known contact attributes, returning a configurable match score (e.g., strong match or exact match) before any protected action is taken.
You define the authentication criteria based on your risk tolerance and use case. For lower-risk interactions like lead qualification, a strong match may be sufficient. For higher-risk actions like password resets, payment processing, policy changes, or account updates you can require an exact match or stricter verification rules.
By embedding real-time, customizable authentication directly into your call flows, the Authenticate Contact action expands the range of high-trust interactions your AI agents can confidently handle.
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iOS call screening can silently intercept calls, leading to missed conversations. For Progressive and Predictive Dial, iOS Call Screening Detection identifies screening in real time, so your agents can stay on the line to answer screener questions, then either continue the conversation if the contact picks up or leave a personalized voicemail if the call routes to an answering machine.
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Contact data evolves constantly, and without visibility into past states, diagnosing issues can be time-consuming and uncertain. The Audience page now includes contact version history, letting you view how a profile and its attributes looked at any point in time. This makes it easy to audit changes, understand when and why an issue was introduced, and quickly pinpoint the source of inconsistencies.

When routing behavior changes unexpectedly, it can be hard to pinpoint what changed, who changed it, or how to fix it. Routing Rule Versions provide a complete audit trail of every update, so issues are easier to diagnose.
For example, if a recently deployed rule starts sending calls to the wrong team, you can quickly identify the exact change, review earlier configurations, and restore a previous version to return traffic to a known-good state with confidence.
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Journeys evolve over time and now you can see exactly how. With complete journey version history, you can review past configurations, understand what was live at any given moment, and restore a previous version with a single click. This makes it easy to correlate journey changes with performance shifts, troubleshoot unexpected results, or roll back after an experiment.

As teams and processes evolve, one-size-fits-all activity statuses can slow operations down. Activity status management lets you quickly add, edit, delete, and reorder agent activity statuses, giving you the flexibility to adapt workflows, as needed. This provides clear, at-a-glance visibility into agent availability while keeping you in full control of how work gets done.

Agents can now see exactly how much time they've spent Available, Offline, On Break, or in other activity statuses throughout their shift. The breakdown appears in the "Today's Progress" modal on Agent Desktop, helping them manage their productivity. For example, if an agent notices they lost track of time and took too long of a break, they can shorten their next break to compensate.
Draft versions of AI agents let you safely work on and test out a new version of an AI agent, without creating duplicate agents or making risky changes to your live agents.
Capture important customer and AI Agent Action responses as collected variables during AI Agent conversations. Seamlessly reference them throughout the call in speech or in branching logic.
Integrate AI agents more deeply into your existing workflows with more public API endpoints, starting with a set of messaging and branded caller ID endpoints.
As Regal continues to ship new features, we've reorganized the navigation to simplify management of AI agents, human agents, and deployment. Use the new spotlight search or press Cmd + K to quickly find what you're looking for.
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