Regal AI
Regal is the new standard in AI-powered CX for high-consideration businesses. Drive better sales, support, and retention – with way less effort. Build, test, deploy and monitor low-latency, lifelike AI Agents.
- Indexed videos, last 90 days
- 11
- Latest publication
- Sep 8, 2026
- Audience
- ~103 subscribers
- Earliest in this view
- Jul 14, 2026
Latest videos
AI Prompting Isn't the Issue (opens the original)
Read excerpt
AI Prompting Isn't the Issue
What's Your Voice AI Hot Take? (opens the original)
Regal is now on the Five9 Marketplace (opens the original)
Read excerpt
Regal is now available on the Five9 Marketplace through the Five9 AI Agent Connect program, giving Five9 customers a direct path to deploy Regal's AI voice agents inside their existing Five9 contact center environment. Regal.ai is an AI agent platform built for outbound and event-driven customer engagement, including lead qualification, appointment reminders, payment collections, and proactive outreach. Regal's agents resolve 99.5% of conversations without human intervention. With the integratio
Mythos 5 Breach and other AI news (opens the original)
Read excerpt
Mythos 5 Breach, Twilio Report and Five9 Spend
Business Appointment Scheduling with AI Agents (opens the original)
Read excerpt
Appointment no-shows aren't random. They're twice as likely among customers a business never manages to reach before their appointment, and most scheduling teams only track no-show rate, not confirmation rate, which is the number that actually predicts it. In this webinar, Regal's Lex (VP of Growth) and David Sokol (VP of Product) break down why traditional confirmation workflows fail and show how AI voice agents fix the root cause, live, with a full demo of a multi-state appointment confirmatio
Publishing over time
Last 90 days. Choose a month to open its work.
Recurring subjects
Named in the text we hold. One piece can cover several.
Audience
~103 subscribers
Measured Sep 19, 2026
Source's subscribers, not the number who saw an individual piece.
About this data
Counts cover the work we have indexed. Tone needs enough text and a confident classification. Excerpts and episode notes are not full articles or transcripts.
Identity or attribution wrong? Suggest a correction.