Case study · Voice

Insurance — EU · Insurance · EU

An outbound voice agent that holds a real conversation.

End-to-end STT → LLM → TTS pipeline that books callbacks, handles objections, and writes notes back to Salesforce — with sub-1-second p95 latency.

1,400staff hours saved per month

At a glance

Client
Insurance — EU · Insurance · EU
Headline metric
1,400 staff hours saved per month
Deliverables
4 shipped to production
Stack
5+ tools across the build

The challenge, approach & outcome.

  1. Challenge

    An EU insurer was paying a 60-person callback team to handle policy renewals and missed-claim follow-ups. They had a 22% pickup rate, 8% conversion, and a 9-week training ramp per new hire. The team couldn't scale into new markets.

  2. Approach

    Built an end-to-end STT (Deepgram) → Claude → TTS (ElevenLabs) pipeline on LiveKit with sub-1s p95 latency. The agent handles objections from a structured playbook, books callbacks into Calendly, and writes notes back to Salesforce. SOC 2-aligned audit logs on every call.

  3. Outcome

    1,400 staff hours saved per month, 28% conversion lift on renewals, and the agent now runs 18 hours a day across three languages. The human team moved up to complex claims work — and morale went with it.

staff hours saved per month
1,400
conversion lift on policy renewals
+28%
p95 latency, end-to-end
<1s

Deliverables

What we shipped.

  • Voice pipeline
  • Multilingual playbook
  • CRM sync
  • Compliance audit logs

Stack

The tools we used.

  • LiveKit
  • Deepgram
  • Claude Sonnet
  • ElevenLabs
  • Salesforce API

Have a similar problem?

Let's talk about your version of this.

30-minute discovery call. No NDA gatekeeping. We'll tell you straight whether we're a fit.