Doneyli De Jesus

Production agents need more than infrastructure. They need an open source foundation for understanding behavior, evaluating quality, and improving continuously without sacrificing control of their data.

Financial institutions already know how to govern credit models. LLM apps change too fast for that playbook. In 18 minutes we’ll walk a practical pattern used with a top global bank: golden datasets, domain evaluators, a PASS/FAIL deployment gate, and reviewable evidence in Langfuse — so model risk gets traces and scores, not screenshots.

Building an AI agent demo is easy. Getting it into production is hard: you need to know what it actually does, catch it when it goes wrong, and keep improving it. In regulated industries you also have to prove all of that. In this hands-on workshop, Annabell Schäfer and Doneyli De Jesus from Langfuse show how to close that loop, using a banking support agent, Northwind Bank, as the example.

Imagine a major hurricane leaving 600,000 homes in darkness. Every second counts. We'll take you behind the scenes of a real-world disaster recovery, where Tampa Electric used Snowflake Cortex AI to orchestrate a rapid and effective storm response. We'll share the challenge, the solution architecture, and the exact steps taken — from LLMs for text extraction at scale to building a chat-based interface for decision-makers.