Robotic voices failed at therapy intake. Now, realistic agents handle sensitive calls with human empathy.
An AI-native contact center platform provides scalable voice automation infrastructure for enterprises in sectors ranging from healthcare to e-commerce.
The engineering team needed to build automated agents that sounded natural enough for sensitive customer interactions. They struggled to find a voice...
“At Regal, we’ve always believed voice is the most impactful channel for driving customer engagement, retention, and conversion. Partnering with ElevenLabs allows us to bring more expressive, authentic voices into our platform so our customers can build trust, reduce friction, and ultimately drive measurable business results in every conversation.”
Voice AI agent platform for automated customer support and sales interactions.
AI voice synthesis platform for text-to-speech, dubbing, and voice cloning.
Regal's Contact center automation is part of this use case:
Related implementations across industries and use cases
Without emotional warmth, users felt self-conscious during personal AI chats. Expressive text-to-speech made conversations feel human.
Voice integration demanded 400 lines of code. A pre-built framework cuts that to 40, enabling rapid agent deployment.
Manual review of sensitive files took two days. AI agents now finish the work in one hour.
Phone-based onboarding sounded robotic across three languages. Natural AI voices turned calls into conversations frontline workers trust.
Typing friction limited query depth. Now, analysts speak complex requests to screen stocks and analyze filings in real time.
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.
Robotic voices failed at therapy intake. Now, realistic agents handle sensitive calls with human empathy.
An AI-native contact center platform provides scalable voice automation infrastructure for enterprises in sectors ranging from healthcare to e-commerce.
The engineering team needed to build automated agents that sounded natural enough for sensitive customer interactions. They struggled to find a voice...
“At Regal, we’ve always believed voice is the most impactful channel for driving customer engagement, retention, and conversion. Partnering with ElevenLabs allows us to bring more expressive, authentic voices into our platform so our customers can build trust, reduce friction, and ultimately drive measurable business results in every conversation.”
Voice AI agent platform for automated customer support and sales interactions.
AI voice synthesis platform for text-to-speech, dubbing, and voice cloning.
Regal's Contact center automation is part of this use case:
Related implementations across industries and use cases
Without emotional warmth, users felt self-conscious during personal AI chats. Expressive text-to-speech made conversations feel human.
Voice integration demanded 400 lines of code. A pre-built framework cuts that to 40, enabling rapid agent deployment.
Manual review of sensitive files took two days. AI agents now finish the work in one hour.
Phone-based onboarding sounded robotic across three languages. Natural AI voices turned calls into conversations frontline workers trust.
Typing friction limited query depth. Now, analysts speak complex requests to screen stocks and analyze filings in real time.
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.