It support · Production

Everise contains 65% of internal service desk tickets with Retell AI voice bots

The problem

Everise's internal global IT help desk relied on a complex IVR requiring employees to navigate multiple branches, with all unresolved calls going to manual agents. Previous voice bot solutions from Microsoft and AWS produced unnatural, slow, and robotic responses.

First attempt

Previous voice bot deployments using Microsoft and AWS produced responses that were unnatural, slow, and robotic, making them unsuitable for Everise's call center needs.

Workflow diagram · grounded in source
1
Employee calls service desk
trigger
“Everise employees called in from various countries, including the US, India, Guatemala, and the Philippines. The solution needed to cater to the different language preferences and accents of this diverse global team.”
2
Caller identity verified in Workday
integration
“Mindcraft Labs used Retell AI to pass a caller's employee ID into Workday to qualify and identify callers”
3
NLP intent recognition
ai_action
“the voice bot, thanks to its NLP abilities, understands my intent and then branches me into the right place”
4
ServiceNow ticket check
integration
“By integrating with ServiceNow, which Everise uses to manage internal IT tickets, Retell AI's voice agents could recognize whether callers had already created a ticket in ServiceNow or whether a new ticket needed to be connected”
5
Multi-tree routing to use case
routing
“Mindcraft identified six use cases, including account access, software issues, and telephony issues. The team designed a series of multi-tree prompts in Retell AI to identify how the caller's intent mapped onto these issues, with each ac…”
6
Autonomous resolution or transfer
output
“The bot solved 65% of caller issues without needing to transfer the call to a human agent for further assistance”
Reported outcome

Retell AI voice bots contained 65% of internal service desk calls, saved 600 man hours per month, and reduced call wait time by 100% from 5-6 minutes to zero.

Reported metrics
Tickets contained65%
Man hours saved per month600
Reduction in call wait time100%
Call wait time before to after5-6 minutes to zero
Reported stack
Retell AINLPWorkdayServiceNow
Source
https://www.retellai.com/case-study/how-everise-contained-65-of-internal-service-desk-tickets-with-retell-ai
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Retell AI voice bots contained 65% of internal service desk calls, saved 600 man hours per month, and reduced call wait time by 100% from 5-6 minutes to zero.

What tools did this team use?

Retell AI, NLP, Workday, ServiceNow.

What results were reported?

Tickets contained: 65%; Man hours saved per month: 600; Reduction in call wait time: 100%; Call wait time before to after: 5-6 minutes to zero (source-reported, not independently verified).

What failed first in this deployment?

Previous voice bot deployments using Microsoft and AWS produced responses that were unnatural, slow, and robotic, making them unsuitable for Everise's call center needs.

How is this it support AI workflow structured?

Employee calls service desk → Caller identity verified in Workday → NLP intent recognition → ServiceNow ticket check → Multi-tree routing to use case → Autonomous resolution or transfer.

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