customer_support · finance · workflow
Tryg deploys three conversational AI virtual agents across Norway, Denmark, and Sweden for customer and internal support
Insurance complexity left Tryg's customers with unanswered questions about policy wording and product information across three distinct markets, while the company also needed to improve the efficiency of its support staff handling high inbound query volume.
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 · Customer or employee initiates chat
A customer or employee initiates a conversation with a conversational AI-powered virtual agent for insurance or internal support.
Tools used
boost.ainatural language understanding
Outcome
Mia automated 80% of customer cases with over 200,000 conversations in 2020; Rosa answered correctly in 95% of cases while logging more sessions than calls to the back office; and Ebbe was deployed to the Swedish market in just 3 weeks despite an original six-month timeline.
Results
Time saved3 weeks
Volume80%
Running sinceAugust 2018
Grounding & classification
Source type: vendor customer story
36 fields verified against source quotes.
agent assistchatbotconversational aiknowledge searchrecommendation systemknowledge basepolicy documenthuman review describedmetric backednamed customerproduction runtime claimedtools describedvendor confirmedworkflow describedinsuranceautomation ratecustomer satisfactiondeflection rateemployee productivityvendor customer storyclaims processingcustomer supporthr onboardingautonomous resolutionescalation workflow