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.
Peak season required 300 temps to manage 9,000 daily cases. An AI agent now handles the volume across 19 countries with zero backlog.
Logistics delays triggered 40k inquiry spikes. An AI agent now resolves 10,000 monthly cases across five languages.
Quarterly compliance updates meant costly reshoots. Now scripts regenerate instantly — no cameras, no vendors, no delays.
Most AI tools addressed one step—code review or a single feature—and couldn't run in-house. Factory covers the full SDLC, on-premise.
One customer, multiple policies, 60+ systems—consistency was out of reach. AI now keeps context intact across voice, WhatsApp, and chat.
Agents juggling fragmented systems and memory for life-safety calls. One platform + AI copilot cut onboarding from 6 weeks to 2.
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.
Peak season required 300 temps to manage 9,000 daily cases. An AI agent now handles the volume across 19 countries with zero backlog.
Logistics delays triggered 40k inquiry spikes. An AI agent now resolves 10,000 monthly cases across five languages.
Quarterly compliance updates meant costly reshoots. Now scripts regenerate instantly — no cameras, no vendors, no delays.
Most AI tools addressed one step—code review or a single feature—and couldn't run in-house. Factory covers the full SDLC, on-premise.
One customer, multiple policies, 60+ systems—consistency was out of reach. AI now keeps context intact across voice, WhatsApp, and chat.
Agents juggling fragmented systems and memory for life-safety calls. One platform + AI copilot cut onboarding from 6 weeks to 2.