Build AI Agents Without Code, Directly From Regal’s Platform

June 11, 2025

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5 min read

For enterprises, successful implementation of Voice AI Agents takes much more than just good tech.

You need the right combination of infrastructure, internal buy-in, smart prompt design, testing, and continuous tuning to get AI Agents performing like your top human agents—and keep them there.

A lot of enterprises are finding themselves caught in the middle of two camps when looking for a way to build Voice AI Agents:

Code-heavy dev platforms: Powerful, but expensive, fragile, and a pain to maintain.
Lightweight builders: Easy to spin up, but too thin to handle real customer workflows.
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Neither path works when your contact center runs thousands of daily conversations, across compliance-heavy channels, with complex routing logic and performance SLAs to match.

That’s why we launched our AI Voice Agent Builder: A no-code tool that lets you build, test, and deploy how your AI Agents sound and act, without the need for developer support.

How are enterprises using this tool? Most commonly, to build AI Voice Agents for lead qualification, appointment scheduling, inbound support, payment collections, and confirmations.

Meet the Regal AI Voice Agent Builder

Voice remains the most powerful channel for customer support and sales. So we wanted to provide a way for our customers to scale voice outreach just as easily and cost effectively as they can scale SMS and chat.

The AI Agent Builder is designed for contact center leaders who know the conversations that convert—and need a way to scale them, without having to rip and replace any current infrastructure.

With Regal’s AI Agent Builder, you can:

Customize everything without code: Tone, voice, conversation logic, fallback flows, custom actions, escalation paths, and more.
Integrate into your existing systems: CRMs, call routing, payments, scheduling platforms, and compliance tools.
Own the end-to-end experience: Test, deploy, monitor, and refine your AI Agents without needing engineering support.
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What Makes Our Builder Different

Our builder is designed to mimic top human performers and plug directly into your existing workflows, so you can scale the behaviors of your most effective agents, with no disruptions to your CCaaS or telephony stack.

Mimic Top Human Performers From Day One

Legacy providers might ask for a million minutes of calls to train up their AI, and it’ll take days if not weeks. To train up Regal AI Voice Agents, all you need to provide is a script and two or three calls.

Regal’s Agent Builder helps you replicate the actions, intuition, and contextual awareness of your best human agents.

We’ll help you train up the AI to mimic the personality, tone, and style in which your best agents answer questions (because the best ones probably go off-script and do things their own way).

We work closely with you to:

Match tone, pacing, and objection handling to your favorite reps.
Personalize interactions based on contact data, account history, and behavioral signals.
Start with a proven script, then build in human-like behavior and flexibility (casual banter or light data-backed “improvisation”).
Make sure the AI is performing workflow tasks and updating your data as needed.
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You know what works, and we know how to replicate it with AI.

Roll Out Voice and SMS Agents in One Platform

Regal gives you a unified builder for both voice and SMS—with shared logic, shared prompts, and shared data—so you’re able to:

Maintain consistent messaging and shared context across channels
Test which channel performs best in different situations (and where channels can be better combined to improve flows)
Reuse flows and content across modalities with minor tweaks
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This helps drive a more seamless omnichannel experience for your leads and customers.

**Built Into Your Workflows, Not Around Them**

Most platforms require you to build in isolation—then either rebuild on the backend to retrofit, or essentially duct tape your agent template to an answering service that’s siloed from your CRM and CCaaS tools.

Regal’s AI Agent builder sits atop a platform that integrates with your CRM, your existing CCaaS/telephony stack, and all of your existing databases. So, you’ll never have to replace or rebuild, and the AI can play really well with your existing human agents.

It’s about matching, mimicking, and scaling—never ripping and replacing.

Workflow Management

Agent workflows are built, tested, and deployed in one place—across Voice and SMS, and across both human and AI interactions.

Two-Way Data Sharing

The info AI Agents collect automatically feeds back into our platform and into your systems. That means:

Cleaner, denser, more automated QA.
More insights to drive future personalization and ongoing improvements.

SIP Integrations

By relying on SIP, Regal AI Agents can pass real-time info and updates off to your live agents when transferring calls—no 30-60 second lag waiting for API calls.

What This Looks Like in Practice

For example, everything the agent hears, says, or captures could be used to do the following:

Personalize the current conversation: If someone started a quote and downloaded your Pro Plan pricing sheet last week, the agent can highlight relevant features and value points during the call.
Pass data to your CRM or CCaaS for next-step automation: Update the contact’s profile with product interest and intent score based on the Pro Plan conversation.
Send a real-time action: Trigger a follow-up SMS offering a limited-time Pro Plan discount.
Train on to improve future interactions: Flag recurring Pro Plan interest to refine qualification prompts and downstream routing.
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Built to Learn and Improve Continuously

Every agent deployed through Regal is backed by robust analytics and A/B testing infrastructure.

That includes:

Real-time reporting on performance, sentiment, conversion, and escalations
Native A/B testing tools—no dev tickets required
Update flows, prompts, and voice settings instantly, with version control and rollback
QA at scale with call summaries, scorecards, and audio transcripts
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This drives faster iteration, and proof on all of those iterations, so you’re always refining everything top-down.

How Does the Builder Actually Work?

Every step of the builder aligns with enterprise use cases—providing the flexibility to support complex voice logic and escalation workflows, compliance requirements, structured data collection, and scale.

Try Regal’s AI Agent Builder

Take a live, self-guided tour through our AI Agent Builder, step-by-step.

Read on below to see some more detail on each step.

1: Select a Channel and (Optional) Templated Use Case

You’ll start by selecting your channel—Voice or SMS. From there, you can either:

Use a pre-built template tailored to common use cases like lead qualification, appointment scheduling, inbound triage, payment collection, or confirmations.
Collaborate with Regal AI experts to define a more bespoke agent.
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Templates are just a starting point—you're never locked in, and you can switch use case or channel at any time.

What this does: Aligns your AI Agent to a clearly defined use case from the start, accelerating testing and deployment. This ensures your logic matches the business objective you're solving for.

2: Create a Persona

Next, define how your agent looks and sounds to the outside world. This includes:

Voice provider and model: Choose from 100+ Regal voice templates or create your own. Regal supports over 20 languages.
LLM selection: Default to OpenAI 4o mini for low-latency, general-purpose tasks. Switch to Claude or OpenAI 4.0 for more nuanced flows.
Fine-tune voice behavior using sliders for:
- Speed: Controls how fast the agent speaks.
- Temperature: Controls emotional variation (more expressive vs more flat).
- Volume: Adjusts output loudness.
- Responsiveness: Sets how quickly the agent replies after hearing the contact.
- Interruption sensitivity: Determines how easily the agent detects and responds to interruptions.
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What this step does: Controls how your agent is perceived—how delicate, emotional, or empathetic they sound. From professionalism and direct, to warm and affirming, the choices you make here can shape caller trust, brand consistency, and overall CX.

3: Define Goals and Tasks

This is where you define the “job description” of your agent. In plain language, you’ll describe:

The agent’s overall goal (e.g. qualify the lead, collect payment, confirm an appointment)
The key steps required to get there
The performance metrics you’ll track as part of meeting those goals (Containment rate, transfer rate, scheduled callback rate, abandon rate, etc.)
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What this step does: Anchors the agent’s behavior and aligns it with distinct business outcomes. Ensures you can track ROI from day one, and gives your team clear benchmarks to improve against.

4: Define How Your Agent Should Act

Again, in plain language, you’re able to provide distinct inputs to govern tone, behavior, and boundaries. You’ll define:

How the agent should handle common questions or objections
Guardrails (what your agent should never say)
Greeting behavior (static greetings vs. dynamic greetings, should the agent speak first or wait for caller)
Style guidance (e.g. “Be concise and professional,” “Encourage hesitant callers,” “Stay on task,” “Always remain empathetic”)
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What this step does: Converts brand voice and frontline best practices into structured logic. This reduces risk (especially in regulated industries), ensures consistency, and lets your agent respond naturally without going off-script.

5: Set Up Two-Way Data Pathways

Configure how the agent uses your existing data to personalize conversations and answer questions accurately, and how it feeds data back into your systems after every interaction:

Add Knowledge Bases (internal wikis, product info, compliance docs, etc.)
Define Custom Actions your agent is allowed to take (e.g. scheduling, payments, transfers, lookups)
Set what context the agent has access to, including:
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- Previous call or SMS history
- CRM objects (e.g. open opportunities, insurance policies, account status)
- Any custom or dynamic fields you currently track
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What this step does: Turns your AI Agent into a node within your full tech stack. The agent doesn’t just talk—it acts, reads context, and updates systems in real-time.

6: Configure On-Call Settings

These are the technical controls that tune the on-call experience and protect against failure modes. You’ll define:

Whether the agent simulates a live call center agent (with optional background noise)
Behavior on contact silence (i.e.should the agent prompt the caller or hang up—and if they prompt, how quickly and how many times should they do so)
Voicemail handling (i.e. should the agent hang up, leave a personalized voicemail, or drop a pre-recorded message)
Fallback voice provider (in case your primary TTS fails, to prevent calls from dropping mid-call)
What data points you want the AI to extract from the conversation (e.g. appointment time, insurance ID, product interest, etc.)
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What this step does: Makes your AI Agent production-safe. These controls reduce dropped calls, improve uptime, and capture the structured data you need to drive future personalization or downstream workflows.

7: Test Your Agent

Now your agent is ready for testing.

You can simulate calls using test contacts, validate logic paths, and observe how the agent handles real inputs—ensuring it behaves exactly as expected across edge cases, objection flows, and data collection points.

This step also ensures all integrations (CRM, calendar, custom actions) are triggering properly, fallback logic is in place, and guardrails are enforced.

Once tested, you can either integrate your agent into existing journeys (add SIP header link when live), or begin testing and building new journey flows across channels.

What this step does: Confirms that your AI Agent performs reliably in real-world scenarios and is fully aligned with your operational infrastructure—before a single call goes live.

Meeting the AI Gap

AI Agents are solving real operational challenges for enterprises across sales, service, and support. But, a lot of platforms either require heavy engineering effort, or offer limited templates that don’t scale well.

Regal’s AI Agent Builder was designed to meet that gap.

It gives enterprises the ability to build agents as capable as their best human reps, without the complexity of a full dev cycle.

You’re not starting from scratch. You’re not settling for off-the-shelf logic. You’re designing agents for your conversations—configured to your systems, your goals, and your customer experience.

If your team is still dealing with missed calls, delayed follow-ups, or clunky handoffs, the path forward is clear: human-like AI, purpose-built for your workflows.

Regal gets you there. And you can start today.

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