Customer support · Production

Revolut deploys ElevenLabs Agents to cut time-to-resolution more than 8x in customer support

The problem

As Revolut expanded globally across nearly 40 markets, the team needed to offer premium voice support at scale without sacrificing cost discipline, compliance, or control—but productionizing the full AI stack in-house proved to be a platform-scale lift.

First attempt

Revolut's internal AI build validated the concept but could not be productionized at scale due to the complexity of speech-to-text, LLMs, TTS, real-time turn-taking, PCI compliance, and zero-retention controls. Other evaluated vendors lacked flexibility, missed reliability targets, or could not match the required voice quality.

Workflow diagram · grounded in source
1
Customer initiates voice support call
trigger
“Revolut deployed ElevenLabs Agents as its first line of voice support for customers in the UK and Europe”
2
Real-time language detection and switching
ai_action
“The ElevenLabs agent handles live calls, detects and switches languages in real time”
3
Secure connection to proprietary systems
integration
“connects securely to proprietary systems to handle three core jobs”
4
Account-specific FAQ and service answering
ai_action
“answer FAQs about accounts and Revolut services with account-specific context, use live customer data to give precise - not generic - responses”
5
End-to-end dispute and chargeback management
ai_action
“wherever possible, manage disputes and chargebacks end to end”
Reported outcome

ElevenLabs Agents cut time-to-resolution by more than 8 times, scaled coverage to more than 4 million customers in more than 30 languages, and achieved a call success rate of more than 99.7% with tickets resolved in less than 5 minutes.

Reported metrics
Time-to-resolution improvementmore than 8 times
Customers covered by voice supportmore than 4 million customers
Languages supportedmore than 30 languages
Call success rateMore than 99.7%
Show all 6 reported metrics
time-to-resolution improvementmore than 8 times
customers covered by voice supportmore than 4 million customers
languages supportedmore than 30 languages
call success rateMore than 99.7%
ticket resolution timeless than 5 minutes
previous agent resolution time comparisonprevious agents took 8x the time or more
Reported stack
ElevenLabs Agentsspeech-to-textlarge language modelstext-to-speech models
Source
https://elevenlabs.io/blog/revolut
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

ElevenLabs Agents cut time-to-resolution by more than 8 times, scaled coverage to more than 4 million customers in more than 30 languages, and achieved a call success rate of more than 99.7% with tickets resolved in l…

What tools did this team use?

ElevenLabs Agents, speech-to-text, large language models, text-to-speech models.

What results were reported?

Time-to-resolution improvement: more than 8 times; Customers covered by voice support: more than 4 million customers; Languages supported: more than 30 languages; Call success rate: More than 99.7% (source-reported, not independently verified).

What failed first in this deployment?

Revolut's internal AI build validated the concept but could not be productionized at scale due to the complexity of speech-to-text, LLMs, TTS, real-time turn-taking, PCI compliance, and zero-retention controls.

How is this customer support AI workflow structured?

Customer initiates voice support call → Real-time language detection and switching → Secure connection to proprietary systems → Account-specific FAQ and service answering → End-to-end dispute and chargeback management.

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