June 2024 Releases

Regal and ElevenLabs bring expressive, multilingual AI voices to customer and sales conversations, adapting tone and emotion in real time to boost conversions, trust, and satisfaction at scale.

Regal Improve gives enterprises a scalable way to analyze thousands of AI agent calls, uncover conversation patterns, pinpoint knowledge gaps, and improve AI performance and customer outcomes over time.

November's releases make it easier to scale your transfer-heavy call flows, with new tools that align dialer pacing to downstream agent capacity and streamline complex handoffs. You’ll also see improved post-call workflow accuracy, with reliable data extraction and disposition outcomes driven by LLM configurability and earlier validation.

Building a great AI voice agent isn’t so different from parenting a five-year-old: clarity, examples, and structure make all the difference. This post breaks down proven prompting principles—from positive framing and persona design to conversational guardrails—that help AI agents sound natural, stay on task, and follow directions every time.

eHealth’s AI agent streamlined Medicare enrollment and support by scaling up for peak call surges, eliminating after-hours wait times, and delivering exceptional experiences for beneficiaries.

Regal is partnering with Cartesia to deliver ultra-low latency, high-fidelity AI voices for enterprise contact centers. Explore new voice options, hear them in action, and learn about Cartesia's industry-leading voice AI offerings.

Regal is partnering with Rime to deliver ultra-realistic, emotionally nuanced AI voices for enterprise contact centers. Discover new voice options that capture human qualities like pacing, resonance, and subtle expression, and learn how Rime’s technology powers conversations that build trust at scale.

‍Customer conversations are inherently dynamic, and Regal Improve’s Knowledge Base Coverage tracks changes in retrieval performance over time and at scale. This makes it easy to verify that KB updates increase coverage and if your documentation is keeping up with evolving customer requests.

Here's our April 2025 product releases, including the early access period for our AI SMS Agents!

Regal’s Knowledge Base feature brings Retrieval-Augmented Generation (RAG) to Voice AI Agents, enabling real-time access to proprietary data for smarter, compliant, and brand-aligned conversations at scale

Worried your AI Agent will say the wrong thing? Well, they might. But find out why that's just a natural part of the process, and how to mitigate the risk of it happening.

In this AI4 fireside chat, Regal.ai COO Sahil Mehta and TaskUs CCO Jarrod Johnson explore how enterprise organizations are deploying voice AI agents across customer experience, support, and sales. They share real-world deployments, discuss quality and ROI trade-offs, and outline best practices for aligning operations and product teams when adopting AI agents at scale.

Our engineering team breaks down how we improved our Voicemail Detection model by aligning the taxonomy with the actual audio, scaling labels, and choosing representations before adding model complexity.

New TCPA updates require interpreting opt-out intent and suppressing outreach across all channels. See how you can use Regal's AI Decision Node to stay compliant.

We ran the latest models from DeepSeek, Anthropic, Google and OpenAI through the Voice CX Benchmark. Here's which ones we're prioritizing for voice AI agents, and which ones we're passing on.

Last month, we shipped releases that improve your contact center operations by extracting business insights with Copilot and reducing wasted agent minutes with our new Voicemail Detection model. The result is more reliable, productive AI agents that can drive revenue for your business.

Copilot started as the place you asked questions. Over the last few months it has become the place where agents are improved, tested, and monitored.

Enterprises need voice agents that hold a natural, human-like conversation while moving each call toward its goal and staying within compliance boundaries. The Voice CX Benchmark scores models on exactly that: how well they progress the call turn by turn, how safely and clearly they communicate, and how quickly they respond.

Every qualifying voice call that runs through Regal gets two sentiment scores: one for the agent, one for the contact. Here's what actually produces those numbers.

Building a voice AI agent from scratch means writing prompts, wiring up actions, and defining guardrails before you can even test a call. Our upgraded agent templates skip that setup.

With Regal’s next-generation Voicemail Detection model, you can now classify voicemail, iOS or Google call screeners as separate categories with very high accuracy. This enables screener-specific handling, ultimately reducing missed agent connections.

Last month, we shipped releases that make it easier to build, monitor, and test agents in one interface. Copilot Canvas brings building, editing, and testing into one interface and it can work straight from your files. Multi-state sticky notes let your team document decisions directly on a live agent.

Copilot now lets your team upload files, like spreadsheets, scripts, and flowcharts, directly as inputs. This gives Copilot the context it needs from the start, making it easier to extend Copilot into new agent use cases as they come up.

How Regal AI Agents recognize, navigate, and continuously improve at getting through third-party IVR phone trees, from classification and the Press Digit action to node isolation and real-world test simulations.

Last month, we launched features that extend your management of AI agents via MCP and CCaaS platforms. Debug based on agent versions or simulation runs, and manage AI analysis data points via Copilot and Regal MCP. As a Five9 AI Agent Connect partner, Regal now has a dedicated integration API built for Voice AI agents.

Copilot Canvas brings agent building, testing, and monitoring into one interface, so you can edit, test, and track performance without leaving Copilot chat.

We've always been careful to never give frontier labs the right to keep or train on customer data. With open weight models, we can go further: when a customer invests in improving these models, that value accrues to them, not to a lab.

Last month, we shipped updates that make AI agents sound more responsive and easier to run at scale. Dynamic Voices lets your agent adjust its pace the second a contact asks for it, and Copilot now handles IVR and disposition management.

OpenAI launched GPT-Live, a new generation of voice models, and described it as a “full-duplex” model. We tested GPT-Live directly to see how the theory holds up in practice.

The Regal Observability Dashboard gives your team real-time visibility into AI agent performance — tracking hallucination rates, guardrail breaches, latency spikes, and more across every call, automatically.

Regal MCP connects your Regal platform to AI environments like Claude, Cursor, and ChatGPT. Your team can pull transcripts, inspect configurations, and trigger actions without switching context.

We reduced end-to-end voice AI response latency by 26% in three weeks by optimizing prompt structure for LLM caching: moving dynamic contact data out of the cacheable prefix so the model stops reprocessing instructions on every call.

This month, we shipped Regal MCP, which extends what your team can build, see, and improve. Regal MCP opens the platform to your external AI environment, so team members can take Regal actions directly from tools like Claude without switching context.

Behind a fragmented and ever-changing regulatory landscape is a simple goal: protecting people from unwanted or poorly timed outreach and giving them control over how they’re contacted. In practice, that responsibility translates into a set of checks that must be validated.

This number is a milestone that represents a fundamental shift in customer experience and how businesses grow. Curious what this number really looks like? We put it into perspective.

Every new LLM comes with trade-offs between latency, cost, and quality — and Regal tests all of them against real voice AI agents. Here's what we found when we ran Gemini 3.5 Flash through our benchmark.

This month, we shipped enhancements that help you quickly make proactive fixes and customize AI agents to your brand. Copilot does more troubleshooting work on your behalf and with headless WebRTC, you can embed Regal voice agents inside your own product UI.

After powering over 400 million calls, we've found that the contact centers that win with voice AI aren't just the ones that deploy first. They're the ones that learn fastest.

AI phone agents aren't just better phone trees. They are autonomous systems that can understand caller intent, retrieve relevant information from your CRM in real time, execute actions, handle objections and clarifications, and complete the conversation without human involvement.

Voice AI is architectural, not cosmetic. Warm words on a broken flow make things worse. But warm words on a well-structured, well-measured system compound over time.

When prospects in healthcare and financial services hear "PII," they often imagine bulk data transfer: the idea that deploying an AI agent means copying a database somewhere. In most modern deployments, that's not what's happening.

At HumanX 2026, Regal's VP of Growth Lex Sivakumar shared what 400 million analyzed calls reveal about voice AI. Customers are not just accepting well-built AI voice agents. They are opening up to them more than they do to humans.

With AI agents, every appointment gets a confirmation call. Each contact gets a chance to reschedule, and the confirmation rate goes to 100%, not because the AI is better at conversations than your agents, but because the AI never runs out of capacity.

AI agent performance depends on how well it aligns with real customer language, not just fluency. Regal Improve helps teams identify gaps and improve outcomes by analyzing real conversations and surfacing high-impact opportunities

In March, we made it faster than ever to build, launch, and continuously improve AI agents with Copilot, Regal's AI agent for building AI agents. Together, these updates lessen the time needed to launch and maintain agents, so you can focus on understanding your customers, unlocking new use cases, and driving faster business outcomes.

Regal is announcing Copilot, our agent for building AI agents. Create, test, deploy, monitor, and improve your Regal AI agents faster than ever by managing an agent instead of going through each step yourself.

American Standard’s AI agents streamlined the home remodeling journey by responding instantly to every homeowner inquiry, capturing demand in real time, and creating a faster, more seamless path from interest to installation.

In February, we made AI agents sound and feel more natural, even when handling complex, multi-step conversations with conditional logic. These updates give you the control to build AI agents that don't just follow a script: they adapt, respond, and engage naturally with each customer. 

The Regal team discusses new research on where Voice AI agents are headed, and why this transformation is far bigger than just cutting costs.

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.

How to build an AI agent that balances empathy with control, and drives real results in production.

Now, you can embed Chat AI directly into your site, providing customers with dynamic, contextual responses that move them toward a decision.

At the AI Summit New York, Regal Director of Product & Product Marketing, Yael Goldstein shared how enterprise organizations are moving beyond theory to deploy Voice AI agents that transform customer experiences.

WebRTC Voice enables real-time voice conversations: instead of dialing phone numbers or switching applications, customers can enable voice conversations directly in your website widget.

December's releases expand where and how you can deploy and scale your AI agents, including a new embeddable website widget for chat and WebRTC. We also released several features to increase observability across the Regal platform.

Leverage real-time decision-making and post-call analysis to increase personalization in your customer interactions, evaluate your agent long-term, and extract insights for continuous improvement. ‍

Every production Voice AI agent is a tradeoff system. Successful Voice AI agents are deliberately constrained, and those constraints can be visualized in The Voice AI Agent Triangle.

Learn about the 2025's product highlights, from the AI Agent Builder to Simulations, deeper observability, and automated insights for continuous improvement at scale.

Celebrate a milestone year as Regal customers scaled AI Agents to 350M calls in 2025, and get a preview of Regal's vision for 2026 to help teams build and improve agents faster, with less effort.

See how modern AI voice agents can match your best human reps by building five core capabilities into every call: spatial awareness, temporal awareness, sensory perception, proactive retrieval, and real action-taking. This post breaks down what each pillar means in practice and how they turn voice AI from a conversational bot into a fully empowered operator.

In this fireside chat, Regal Co-Founder & CEO Alex Levin sits down with Kin Insurance’s Austin Ewell and a360inc’s Henry Davidson to share how their organizations are using AI agents to transform outreach, customer experience, and operational efficiency. They discuss real-world deployments—from qualification and human agent handoffs to complex negotiation workflows—break down the results, and offer practical guidance for leaders adopting AI agents at scale.

See how Aprende transformed student enrollment with Regal’s AI Agent—matching human conversion rates, driving 18X more engaged calls, and saving advisors over 100,000 minutes monthly.

October’s releases give you deeper structure and insight across your AI operations—from designing predictable, multi-state conversation flows and delivering seamless human handoffs to uncovering performance insights and strengthening your agents’ knowledge for continuous improvement.

See how a360inc automated notary outreach and negotiation with Regal’s AI Agent, cutting costs by 80%, saving money on bid collection, and boosting coverage with unlimited outreach, structured negotiations, and reliable data capture.

September’s releases give you greater visibility and control across your AI operations—from monitoring agent action invocations, contact receptiveness to AI, and dialing compliance, to experimenting confidently with the latest LLMs and expanded Simulations coverage.

Introducing Regal’s Multi-State Agent Builder, a purpose-built tool for orchestrating complex, non-linear conversations. Gain full control over prompts, logic, and actions to scale AI agents with accuracy, personalization, and enterprise reliability.

Learn about the difference between single-state and multi-state AI agents, and how each impacts speed, scale, and reliability. Discover when simplicity is enough and when enterprise workflows demand structured orchestration, so you can choose the right design for your use case.

Trace the evolution of AI agents, from scripted chatbots to IVR systems to single-state GenAI, and now to multi-state agents that unlock true end-to-end orchestration at scale.

Explore the six testing capabilities that ensure voice AI agents deliver consistent, trustworthy customer experiences at scale.

See how to test AI Voice Agents in Regal with simulation-based suites, manual checks, and end-to-end validations. Ensure logic, voice, and telephony all perform reliably so every deployment scales with confidence.

Learn how to measure AI Agent success in Regal with real-time dashboards, KPI reporting, and custom analysis. Get full visibility into performance, customer experience, and business impact—so every deployment drives results.

Discover how you can use Simulations to evaluate scenario-specific conversational flows that pinpoint AI Agent failures before launch. Speed up regression testing, validate prompts, knowledge bases, and custom actions at scale, and deploy reliable AI Agents with confidence.

New features include automated test evaluations, the Regal Improve insights dashboard, PII-safe recording actions, 25 ultra-realistic voice options, bulk Knowledge Base URL upload, and expanded quiet hours compliance—designed to accelerate iteration, improve agent performance, and safeguard customer trust.

Apple’s iOS 26 introduces new call-screening controls that will reshape outbound performance. This guide explains what’s changing, how adoption may impact enterprise contact centers, and the proactive steps leaders can take now to protect answer rates and customer trust.

Learn how to structure a knowledge base that keeps AI Agents accurate and on-script. Discover why human-style KBs fail, and apply best practices like single-topic chunking, concrete instructions, and explicit outcomes to reduce hallucinations and scale reliable RAG performance.

Learn how to maintain a clean, reliable RAG system for AI Agents. Discover best practices for structuring source docs, chunking content, titling for retrieval, avoiding redundancy, and keeping knowledge bases fresh to ensure accurate, scalable performance.

Discover how Regal’s AI Simulations eliminate manual QA bottlenecks for enterprise AI agents. Auto-generate test cases, run bulk end-to-end conversations in seconds, and validate performance at scale before any live calls are made.

Introducing five new real-time AI Agent metrics, giving you real-time visibility into transfers, conversation quality, and customer receptiveness to AI.

Learn how Regal turns unstructured AI Agent transcripts into actionable business intelligence. Discover patterns, pinpoint performance gaps, and update prompts or knowledge bases to improve customer experience at scale.

Regal’s Custom AI Analysis transforms post-call transcripts into actionable, structured data points, so you can personalize follow-ups, analyze trends in-aggregate, and scale improvements across every interaction.

New features include AI-powered conversation simulations, custom post-call analysis, voicemail configuration options, real-time metrics, and full transcript exports, all designed to improve AI Agent performance and compliance.

If you missed our H2 Roadmap Reveal, here are the biggest takeaways, including real customer wins and a preview of what’s coming in the second half of the year.

Master context engineering by choosing the right method for AI agent knowledge—prompts for behavioral control, RAG for long-form, unstructured data, and custom actions for precise lookups.

Lessons from the frontlines on how to build AI Voice Agent-ready APIs.

Learn how to tune AI voice agents for sales, compliance, and customer experience. Explore Regal’s voice parameters, like speed, tone, temperature, responsiveness, to optimize conversion, clarity, and trust at scale.

This guide outlines the capabilities, trade-offs, and real-world applications of every model currently supported in Regal.

This article outlines the core characteristics that influence how voice AI is perceived on live calls. From mechanical traits like speed and volume, to more emotional and conversational behaviors, we’re going to look at what those characteristics mean, why they matter, and how they impact your bottom line.

Learn how to configure your AI Voice Agent for real performance. This guide covers the most important voice settings in Regal, what ranges top brands use in production, and how adjusting speed, tone, and responsiveness impact cost, containment, and overall customer experience.

June’s releases give you more control to test, improve, and scale AI agents—while also making life easier for human agent teams. From real-time debugging tools to capacity control and a floating Chrome extension, we’re unlocking faster workflows, better control, and stronger performance across the board.

Learn how RAG transforms AI Agent performance by retrieving real-time customer and contact data—ensuring every Voice AI Agent response is unique to your business, contextual, and compliant.

Discover how you can now staff Regal’s progressive dialer with AI Voice Agents—to run high-volume outbound campaigns with smarter pacing, instant call connection, and voicemail detection—boosting efficiency and eliminating abandoned calls.

Learn how to use SIP headers with Regal AI Voice Agents to personalize routing, enrich transfers, and integrate with your existing telephony stack—no backend changes required.

Discover how Regal's AI Agent Builder lets enterprises create and deploy custom Voice AI Agents without code, integrate with existing systems, and scale workflows to deliver human-like customer interactions at scale.

Learn how SIP integration enables enterprises to connect Regal Voice AI Agents to existing CCaaS platforms, pass call context in real time, and deploy voice AI without infrastructure changes.

May’s releases unlock more conversations with AI Agents through smarter dialing, automatic callback scheduling, and native calendar booking to boost connect rates and accelerate follow-ups.

Discover how AI appointment setter technology is being adopted by enterprises in industries like healthcare, insurance, and education as a strategic advantage for scaling operations and improving customer satisfaction.

Explore how automated phone systems are transforming enterprise communication strategies. Learn how to avoid common pitfalls, optimize customer journeys, and achieve ROI through strategic deployment across industries like healthcare, insurance, and education.

The best customer experiences are seamlessly omnichannel. In this guide, see how Regal enables seamless, AI powered omnichannel support across voice and SMS.

Learn how to design AI phone agents that prevent frustration, earn trust, and actually help customers—by getting the voice, logic, and data right from the start.

With the right design and controls, AI agents can be built to deliver empathetic, human-like interactions for all of your routine contact center interactions.