Customer support · Production

LifeScan delivers personalized customer care with Aisera's AI Agent Platform

The problem

LifeScan's support operations were heavily reliant on manual, reactive processes that could not keep pace with a rapidly growing customer base of over 4.7 million users, resulting in long wait times, increased agent fatigue, and an inability to provide timely around-the-clock service.

Workflow diagram · grounded in source
1
Customer inquiry arrives
trigger
“we can now quickly resolve customer inquiries in seconds through self-service”
2
RAG and LLM knowledge retrieval
ai_action
“Leveraging domain-specific LLMs for healthcare and retrieval augmented generation (RAG), the OneTouch® Assistant provides personalized, scalable support”
3
AI automates key support tasks
ai_action
“automates key tasks such as troubleshooting and order management, cutting response times from days to seconds”
4
24/7 self-service resolution
output
“ensuring 24/7 self-service for LifeScan's growing customer base”
Reported outcome

The OneTouch® Assistant automated 65% of incoming support requests, saved $2.2 million, improved customer satisfaction (CSAT) by 70%, and cut response times from days to seconds while reducing redundant inquiries and alleviating agent fatigue.

Reported metrics
Auto-resolution rate65%
Cost savings$2.2M+
Customer satisfaction improvement70%
Response timefrom days to seconds
Reported stack
Aisera AssistantRAGdomain-specific LLMs
Source
https://aisera.com/customers/lifescan
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

The OneTouch® Assistant automated 65% of incoming support requests, saved $2.2 million, improved customer satisfaction (CSAT) by 70%, and cut response times from days to seconds while reducing redundant inquiries and…

What tools did this team use?

Aisera Assistant, RAG, domain-specific LLMs.

What results were reported?

Auto-resolution rate: 65%; Cost savings: $2.2M+; Customer satisfaction improvement: 70%; Response time: from days to seconds (source-reported, not independently verified).

How is this customer support AI workflow structured?

Customer inquiry arrives → RAG and LLM knowledge retrieval → AI automates key support tasks → 24/7 self-service resolution.

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