Customer support · Production

Neptune Flood reduces cost per ticket by 78% and resolution time by 92% with Ada conversational AI

The problem

Neptune Flood's Customer Success team handled large volumes of inbound emails and phone calls each month and needed to scale support for a growing customer base — including complex insurance flows like policy cancellations — without rising costs.

Workflow diagram · grounded in source

Customer submits inquiry via Ada

trigger

“Customers were able to leverage Ada to submit their claim at a time that was most convenient to them, even in the middle of the night”

Bot collects information in one conversation

ai_action

“the bot collects all the necessary information in one conversation to complete the request or hand it off to the Neptune Flood team for review and verification”

API integration for complex flows

integration

“By integrating its homegrown APIs into Ada's flows, Neptune Flood is able to provide unique experiences for insurance agents and policyholders”

Route by audience and authentication

routing

“They're also able to differentiate experiences for authenticated users vs non-authenticated—the claims process, for example, is available to anyone on the main site, whereas policy changes can only be made by authenticated (i.e., logged …”

Human handoff for complex requests

human_review

“Even the inquiries that require a human touch are that much easier to solve now because Ada collects the relevant information up front; customer success agents are able to quickly review and solve the request”

Reported outcome

Ada enabled Neptune Flood to reduce cost per ticket by 78%, decrease ticket resolution time by 92%, and save $100k in the first year.
During Hurricane Ian, 30–35% of claims were submitted through the bot, and Neptune Flood's staff evacuated safely while service continued uninterrupted.

Reported metrics

Bot containment rate achieved30%

Time to reach 30% containment vs goal30 days instead of 90-day goal

Savings described as compoundingsignificant savings that will compound over time

Reported stack

AdaZendeskZoom

Source

https://www.ada.cx/case-study/neptune-flood

Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Ada enabled Neptune Flood to reduce cost per ticket by 78%, decrease ticket resolution time by 92%, and save $100k in the first year.

What tools did this team use?

Ada, Zendesk, Zoom.

What results were reported?

Bot containment rate achieved: 30%; Time to reach 30% containment vs goal: 30 days instead of 90-day goal; Savings described as compounding: significant savings that will compound over time (source-reported, not independently verified).

How is this customer support AI workflow structured?

Customer submits inquiry via Ada → Bot collects information in one conversation → API integration for complex flows → Route by audience and authentication → Human handoff for complex requests.

Ada enabled Neptune Flood to reduce cost per ticket by 78%, decrease ticket resolution time by 92%, and save $100k in the first year.During Hurricane Ian, 30–35% of claims were submitted through the bot, and Neptune Flood's staff evacuated safely while service continued uninterrupted.