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Regal

by Regal.AINew York CityNo ratings yet

Voice AI agents for enterprise contact centers

Visit regal.ai

Linked from regal.ai · checked 29 Oct

Tool type
Voice AI agent platform
Made for
Enterprise contact center teams
Runs on
Phone calls with contact center integrations
Agents answer and place phone calls; configuration happens in a web platform that connects to existing contact center and CRM systems.
Last checked
29 Oct 2026
1 product sources

What it does

Regal provides voice AI agents that answer and place phone calls for businesses. Agents take in live caller speech plus CRM or scheduling data and carry out spoken conversations to qualify leads, book and reschedule appointments, send reminders, handle customer support, and run collections. Teams can monitor calls in real time, set goals, and use automated quality assurance.

Most teams start with one agent for a single use, such as inbound support or appointment booking, then expand across the contact center. The platform offers drag-and-drop workflow building and native A/B testing of agent versions. Implementation is supported by a Forward Deployed Engineering team, and existing contact center software and CRMs connect through integrations, APIs, and webhooks.

Regal is designed for enterprise and mid-to-large contact centers, including teams in insurance, healthcare, financial services, education, and home services. Getting started means requesting a demo, followed by sales-led onboarding. Regulated use cases involve compliance boundaries that should be reviewed with the vendor before launch.

What it can do

  • Handle inbound support and outbound lead qualification calls with AI voice agents
  • Schedule, confirm, reschedule, and send reminders for appointments
  • Run collections and payment-recovery calls
  • Monitor live calls and set goals with Conversation Intelligence and automated QA
  • Build agent workflows with drag-and-drop orchestration and run native A/B tests
  • Personalize calls using real-time customer and CRM data

Works with

  • Contact center (CCaaS) and CRM integrations; the company references 40+ integrations
  • APIs and webhooks for custom connections

Example workflows

Inbound appointment booking
Input: a caller asks to book a service appointment. Steps: the agent answers immediately, checks availability, and books into the connected scheduling system. Output: a confirmed booking recorded in the scheduling system.
Outbound lead qualification
Input: a list of inbound web leads. Steps: the agent calls each lead, asks qualifying questions, and routes qualified prospects to a human or books time. Output: qualified leads or booked meetings with structured call outcomes.

Before you choose

  • Performance figures on the website (such as 97% containment and 80% cost reduction) are company-reported.
  • Regulated use cases such as insurance and financial services involve compliance boundaries to review with the vendor.
  • Current pricing and the full integration list are available from the vendor directly.

Listed under

Get started

Book a personalized demo through the website; onboarding is sales-led with Forward Deployed Engineering support.

  1. Request a demo through the Regal website to scope the use case.
  2. Work with the Forward Deployed Engineering team to design and customize the agent for your company and customers.
  3. Connect the agent to your existing contact center software and CRM through the available integrations, APIs, or webhooks.
Request a demo

Plans and prices

Check https://www.regal.ai/pricing directly for current plan terms.

We couldn’t find published prices for Regal. See their pricing page ↗

Sources for this overview

Product pages, documentation, and pricing checked 29 Oct 2026. Each source supports part of the overview; availability and prices can change.

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Where this comes from

How we research
Company website
regal.ai: product, pricing and policy pages
YC directory mirror
Batch and company name
Human review
Checked by a person
knowledge_base

Last checked 29 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.