customer_support · finance · workflow

DNB transforms internal customer service operations with Juno, a conversational AI virtual agent for agent-facing knowledge access

DNB's customer service agents and banking advisors faced delays in assisting customers because the previous document management system required them to manually search for routines, making it inefficient and time-consuming.

How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Agent opens Juno chatbot
DNB launched Juno to assist agents and advisors in quickly and easily accessing the routines they need when helping customers.
Tools used
boost.aiJuno
Outcome

Juno replaced the previous data management system entirely and became the exclusive tool for agents to access routines, reaching 1,200 daily active users, 80,000 conversations per month, and over 2 million questions answered in 2022.

Results
Time saved80,000
Volume1,200
Running sinceMarch 2020
Source

https://www.boost.ai/case-studies/how-dnb-transformed-customer-service-operations-and-enhanced-human-agent-efficiency-with-conversational-ai

How we source this →

Grounding & classification
Source type: vendor customer story
29 fields verified against source quotes.
agent assistchatbotconversational aiknowledge searchknowledge basehuman review describedmetric backednamed customerproduction runtime claimedtools describedworkflow describedbankingemployee productivityresponse time reductionthroughput increasevendor customer storyback office opscustomer supportextract classify routerag answering