Ticket transfers between teams delayed support. Now, AI routes queries by theme and surfaces suggested answers for human agents.
A publicly traded financial technology platform provides end-to-end global payments capabilities for enterprise clients like Meta, Uber, H&M, and Microsoft.
Increasing transaction volumes placed immense pressure on support operations as the company sought to scale without expanding headcount. Passing...
“We are engineers so we are always looking at ways to scale our business using technology without having to increase the team size.”
Unified payment processing and financial technology platform for global enterprises.
Framework and developer platform for building LLM-powered applications.
Adyen's Customer support is part of this use case:
Related implementations across industries and use cases
Escalations from 2.5M daily transactions bottlenecked teams. Multi-agent AI now dynamically routes and resolves complex payment issues.
Rigid rules slowed complex queries. An AI agent now tracks card deliveries and answers 90% faster, resolving 70% of cases.
Complex disputes required manual tracing. AI agents now autonomously plan and execute multi-step payment investigations.
Rigid rules slowed complex queries. An AI agent now tracks card deliveries and answers 90% faster, resolving 70% of cases.
Agents manually hunted for crypto data. Now, an autonomous agent cites real-time records to boost case resolution by 70%.
Strict privacy rules prevented sending raw call transcripts to AI. Now, an automated system safely strips and restores sensitive data.
Escalations from 2.5M daily transactions bottlenecked teams. Multi-agent AI now dynamically routes and resolves complex payment issues.
Basic troubleshooting consumed agents' time. Now, an AI fluent in local dialects independently resolves 73% of these cases.
Manually evaluating high call volumes was slow and inaccurate. Now, AI extracts sentiment so sales teams can refine their outreach.
Ticket transfers between teams delayed support. Now, AI routes queries by theme and surfaces suggested answers for human agents.
A publicly traded financial technology platform provides end-to-end global payments capabilities for enterprise clients like Meta, Uber, H&M, and Microsoft.
Increasing transaction volumes placed immense pressure on support operations as the company sought to scale without expanding headcount. Passing...
“We are engineers so we are always looking at ways to scale our business using technology without having to increase the team size.”
Unified payment processing and financial technology platform for global enterprises.
Framework and developer platform for building LLM-powered applications.
Adyen's Customer support is part of this use case:
Related implementations across industries and use cases
Escalations from 2.5M daily transactions bottlenecked teams. Multi-agent AI now dynamically routes and resolves complex payment issues.
Rigid rules slowed complex queries. An AI agent now tracks card deliveries and answers 90% faster, resolving 70% of cases.
Complex disputes required manual tracing. AI agents now autonomously plan and execute multi-step payment investigations.
Rigid rules slowed complex queries. An AI agent now tracks card deliveries and answers 90% faster, resolving 70% of cases.
Agents manually hunted for crypto data. Now, an autonomous agent cites real-time records to boost case resolution by 70%.
Strict privacy rules prevented sending raw call transcripts to AI. Now, an automated system safely strips and restores sensitive data.
Escalations from 2.5M daily transactions bottlenecked teams. Multi-agent AI now dynamically routes and resolves complex payment issues.
Basic troubleshooting consumed agents' time. Now, an AI fluent in local dialects independently resolves 73% of these cases.
Manually evaluating high call volumes was slow and inaccurate. Now, AI extracts sentiment so sales teams can refine their outreach.