ticket_triage · finance · workflow
Adyen builds LLM-powered smart ticket routing and support agent copilot with LangChain
Growing merchant volume and transaction load put rising pressure on Adyen's support teams, and ticket hand-offs between teams were a primary driver of slower response times. The team wanted to scale support capacity through technology without growing headcount.
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 · Merchant submits support ticket
A support ticket enters the routing system to be directed to the right support person based on its content.
Tools used
LangChainLangSmithvector databaseembedding modelKubernetes
Outcome
Adyen's LLM-driven ticket routing and copilot made support agents more efficient and satisfied, with document retrieval far outperforming traditional keyword-based search and immediately establishing team trust in the new system.
Results
Time saved4 months
Grounding & classification
Source type: vendor customer story
30 fields verified against source quotes.
agent assistdocument classificationknowledge searchragsentiment analysisknowledge basesupport tickethuman review describednamed customerproduction runtime claimedtools describedvendor confirmedworkflow describedfinancial servicesaccuracy improvementemployee productivityresponse time reductionvendor customer storycustomer supportticket triageai draft human approvalextract classify routerag answering