Building AI-powered customer support in fintech isn’t just about integrating ChatGPT. It requires careful risk management, continuous impact validation, and pragmatic product decisions.
In this talk, I’ll share how we built and rolled out automated chat support at Wise for its 15M+ customers over the past year - evolving from simple ML classification to full conversational agents. You’ll learn how we balanced innovation with caution in a regulated environment where mistakes can have high consequences.
What You’ll Learn:
- Incremental delivery strategies: How to ship AI capabilities step-by-step while proving value at each stage, rather than disappearing for months to build the perfect solution
- Data-driven decision making: Using metrics to validate each evolution and know when to move forward
- Risk management in production: Navigating compliance reviews, managing risks, and building safety nets for when things go wrong
- Build vs. Buy tradeoffs: When to partner with specialized providers and when to invest in custom solutions - and how to do both simultaneously
- Making AI work for your domain: Context engineering, knowledge base design, and adapting general-purpose LLMs to specific business needs
This isn’t a story about perfect execution - it’s about pragmatic product engineering in the real world, where you need to deliver value continuously while working toward ambitious goals.
