Customer support · Production

Global telehealth company reduces peer-to-peer Slack questions 16% with Guru Benefits AI Agent

The problem

Customer-facing operations teams at a global telehealth company had to manually synthesize answers from scattered fine-print documents, SOPs, Google Drive folders, and Slack threads — a time-consuming process that became unsustainable at scale and carried serious medical, financial, and legal accuracy risks.

Workflow diagram · grounded in source
1
Support rep submits question
trigger
“Their customer-facing operations teams field complex, sensitive questions where inaccurate answers carry serious medical, financial, and legal consequences”
2
Organization name required
validation
“required an organization name in every question before the agent would proceed. This single constraint dramatically improved accuracy by forcing the agent to anchor every answer to a specific client's program documents”
3
Citation-first AI response
ai_action
“We really focused on citations over summarization. We customized our agent prompt to cite where it found information to answer the question, not just create a general summary of an answer based on multiple sources”
4
Rep reviews output
human_review
“to review the output and then decide if they need to look deeper”
5
Daily SME quality assurance
validation
“two SMEs conduct daily QA. When an inaccurate answer is flagged, the team corrects the information”
6
Knowledge gaps feed training
feedback_loop
“The daily QA process has surfaced knowledge gaps that are improving training programs — turning the agent into a diagnostic tool for organizational learning, not just a support accelerator”
Reported outcome

The Benefits AI Agent drove a 16% reduction in peer-to-peer Slack questions company-wide, handles over 700 questions per month, and Guru AI super-users show 17% higher productivity, with new hires who actively used the agent ramping faster than their peers.

Reported metrics
peer-to-peer Slack question reduction16%
questions per month to Benefits AI Agent700+
Guru AI super-user productivity17%
Reported stack
GuruBenefits AI AgentGuru's AI editing toolsGoogle DriveSlack
Source
https://www.getguru.com/customers/global-healthcare-company
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

The Benefits AI Agent drove a 16% reduction in peer-to-peer Slack questions company-wide, handles over 700 questions per month, and Guru AI super-users show 17% higher productivity, with new hires who actively used th…

What tools did this team use?

Guru, Benefits AI Agent, Guru's AI editing tools, Google Drive, Slack.

What results were reported?

peer-to-peer Slack question reduction: 16%; questions per month to Benefits AI Agent: 700+; Guru AI super-user productivity: 17% (source-reported, not independently verified).

How is this customer support AI workflow structured?

Support rep submits question → Organization name required → Citation-first AI response → Rep reviews output → Daily SME quality assurance → Knowledge gaps feed training.

Related customer support cases