How Canva built an Agentic Support Experience using Langfuse Observability

At Canva, our support experience is powered by multiple AI systems, from real-time assistance to asynchronous ticket resolution that handles complex, multi-step workflows and escalates to humans when needed. In this talk, we’ll share how we took these systems from MVP to serving Canva’s 250M+ users, and the infrastructure we built along the way to get there safely.

We’ll cover how traces helped us debug complex agent workflows, how prompt management unlocked safe iteration through shadowing and localisation, and how we built continuous evaluation loops using LLM-as-judge, offline datasets, and human feedback, using tools like Langfuse alongside internal tooling we developed.

We’ll also share practical lessons from running experiments, replaying real support scenarios, and the things we wish we’d known earlier about scaling AI systems in production.