Revolut deploys ElevenLabs Agents to cut time-to-resolution more than 8x in customer support
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.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Customer initiates voice support call
ElevenLabs Agents serve as the first line of voice support for customers in the UK and Europe.
Tools used
ElevenLabs Agentsspeech-to-textlarge language modelstext-to-speech models
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.
What failed first
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.