Klarna has reshaped global commerce with its consumer-centric, AI-powered payment and shopping solutions. With over 85 million active users and 2.5 million daily transactions on its platform, Klarna is a fintech leader that simplifies shopping while empowering consumers with smarter, more flexible financial solutions.
Klarna’s flagship AI Assistant is revolutionizing the shopping and payments experience. Built on LangGraph and powered by LangSmith, the AI Assistant handles tasks ranging from customer payments, to refunds, to other payment escalations.
With 2.5 million conversations to date, the AI Assistant is more than just a chatbot; it’s a transformative agent that performs the work equivalent of 700 full-time staff, delivering results quickly and improving company efficiency.
The Challenge: Scaling Customer Support & Handling Escalations
Overcoming escalation overload
Klarna faced growing challenges in managing multi-departmental escalations. To meet rising consumer expectations, Klarna needed a solution that could combine speed, accuracy, and accessibility while scaling across global markets.
"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."— Sebastian Siemiatkowski, CEO and Co-Founder, Klarna
The Solution: Powered by LangGraph and LangSmith
A partnership driving precision and performance
Klarna turned to LangGraph and LangSmith to evolve their AI Assistant into a reliable, scalable multi-agent system. Key improvements included:
- Controllable agent architecture: Klarna’s AI assistant routed requests and handled different tasks using the LangGraph framework. This helped decrease latency, improve reliability, and cut operational costs.
- Context-aware intelligence: By dynamically tailoring prompts to specific scenarios, Klarna ensured that their AI assistant consistently delivered relevant, context-aware responses while reducing token costs and latency.
- Test-driven development: With LangSmith, Klarna could pinpoint what issues arose by seeing step-by-step how their AI assistant behaved. Leveraging LangSmith, Klarna rigorously tested critical use cases for their AI assistant, then validated and refined agent performance with LLM evaluations and prompt iteration.
- Prompt optimization: Klarna’s insights in turn improved LangSmith’s prompt engineering features – notably, Klarna helped inspire and design advanced capabilities like meta-prompting. Meta-prompting allows users to suggest specific improvements to the prompts, by prompting them and seeing how the optimized prompt impacted response quality.
The Impact
Built with LangGraph and refined with LangSmith, Klarna’s AI assistant has empowered their teams to handle customer escalations more effectively. They’ve achieved the following results in the past 9 months:
- Faster resolutions: Reduced average customer query resolution time by 80%, enabling faster responses to user queries and saving analysts and engineers hours a week of investigation time.
- Increased AI automation for chat handling: Automated ~70% of repetitive support tasks, freeing up customer service agents to handle complex, high-value interactions
- Improved accuracy: Improved root cause identification for rejection, leading to a significant reduction in customer escalations.