AI agents for insurance

Common use cases

What teams in insurance automate first

Every one of these is a real agent conversation, running in the channel the customer started in.

The claim opened, evidence collected, the excess stated from real policy terms, and the repair booked, with a claims handler adding entitlements.

Am I covered, answered from the actual policy: the glass excess, the no-claims impact, the approved fitter booked to come to the driveway tomorrow.

The renewal quote explained, dead cover from an old rental dropped, and the policy renewed at a lower price without touching core protection.

Damage photos and the other driver’s details collected by text, read and confirmed in-thread, and the claim moved to assessment the same afternoon.

Insurance teams building on Voiceflow

Risk and compliance

Production volume, and the certifications to run it on regulated data.

99.95

Agent uptime

Voiceflow latency

300

Messages per minute scale

Voiceflow hands off to your human team with the full conversation, so nobody asks the customer to start again.

There is no migration project. Voiceflow sits on top of the CX stack you already run, and speaks to anything else through the API.

Most insurers are live on their existing helpdesk the same day, with no change to policy or claims systems.

How do we keep coverage answers accurate?

Answers are grounded in your approved policy documents, and anything outside that scope escalates instead of being invented.

Can agents open real claims?

Yes — agents write to your claims system through your integration layer, with the transcript retained as part of the file.

What about licensed advice?

Agents are scoped to servicing and information. Anything requiring a licensed decision routes to a human with context attached.