Escalations from 2.5M daily transactions bottlenecked teams. Multi-agent AI now dynamically routes and resolves complex payment issues.
A global fintech platform managing over 85 million active users and processing 2.5 million daily transactions across international markets.
Managing complex, multi-departmental support escalations across global markets created significant operational bottlenecks. The organization needed a...
“LangChain has been a great partner in helping us realize our vision for an AI-powered assistant, scaling support and delivering superior customer experiences across the globe.”
Global payment provider and bank for buy now, pay later and shopping services.
Framework and developer platform for building LLM-powered applications.
Klarna's Multi-agent customer support is part of this use case:
Related implementations across industries and use cases
Ticket transfers between teams delayed support. Now, AI routes queries by theme and surfaces suggested answers for human agents.
Building voice AI in-house proved too complex. Now, agents resolve disputes and support calls for 4 million customers.
35M customers waited in queues for payment updates. Now, a voice agent resolves routine calls instantly, leaving complex issues to humans.
Human support faced peak-hour delays as this European grocer scaled. Now, a multilingual AI agent edits orders and issues credits 24/7.
Peak season required 300 temps to manage 9,000 daily cases. An AI agent now handles the volume across 19 countries with zero backlog.
Strict privacy rules prevented sending raw call transcripts to AI. Now, an automated system safely strips and restores sensitive data.
Analyzing 200-page reports took senior reps hours. Now, AI extracts key insights, empowering any sales rep to build tailored client decks.
Manually evaluating high call volumes was slow and inaccurate. Now, AI extracts sentiment so sales teams can refine their outreach.
Manual call evaluations delayed insights by weeks. Now, bots score calls at scale, empowering analysts to synthesize data in hours.
Escalations from 2.5M daily transactions bottlenecked teams. Multi-agent AI now dynamically routes and resolves complex payment issues.
A global fintech platform managing over 85 million active users and processing 2.5 million daily transactions across international markets.
Managing complex, multi-departmental support escalations across global markets created significant operational bottlenecks. The organization needed a...
“LangChain has been a great partner in helping us realize our vision for an AI-powered assistant, scaling support and delivering superior customer experiences across the globe.”
Global payment provider and bank for buy now, pay later and shopping services.
Framework and developer platform for building LLM-powered applications.
Klarna's Multi-agent customer support is part of this use case:
Related implementations across industries and use cases
Ticket transfers between teams delayed support. Now, AI routes queries by theme and surfaces suggested answers for human agents.
Building voice AI in-house proved too complex. Now, agents resolve disputes and support calls for 4 million customers.
35M customers waited in queues for payment updates. Now, a voice agent resolves routine calls instantly, leaving complex issues to humans.
Human support faced peak-hour delays as this European grocer scaled. Now, a multilingual AI agent edits orders and issues credits 24/7.
Peak season required 300 temps to manage 9,000 daily cases. An AI agent now handles the volume across 19 countries with zero backlog.
Strict privacy rules prevented sending raw call transcripts to AI. Now, an automated system safely strips and restores sensitive data.
Analyzing 200-page reports took senior reps hours. Now, AI extracts key insights, empowering any sales rep to build tailored client decks.
Manually evaluating high call volumes was slow and inaccurate. Now, AI extracts sentiment so sales teams can refine their outreach.
Manual call evaluations delayed insights by weeks. Now, bots score calls at scale, empowering analysts to synthesize data in hours.