Tom Konewka

Conversational AI is making it much easier to understand what’s changing in your data. The harder problem now is acting on the signals that shape high-stakes business decisions early enough to reduce missed targets, operational disruption or compliance exposure. In this lightning session, we’ll demo how those signals can move from explanation to action inside Databricks Genie Spaces using Retool agents directly on governed enterprise data. A question in Genie becomes a shared response that brings in the right stakeholders and triggers follow-up steps across systems directly from the same workspace. You’ll see how acting on signals earlier can help your teams adjust plans sooner, resolve issues faster and influence the decisions that matter most.

Reckitt operates a global portfolio of health and hygiene brands across more than 60 countries, including brands like Lysol and Durex, where speed, agility, and efficiency are critical to staying competitive. After building its Gen AI platform on Databricks, the company set out to deliver faster, more actionable consumer insights to marketing teams as part of a broader business transformation, ultimately reducing insight delivery time by up to 60 percent. In this session, Retool shares how Reckitt unified marketing data across sources and embedded Gen AI directly into governed marketing workflows on the Databricks Lakehouse, replacing manual reporting with execution paths that scale. Attendees will gain practical insights into the business and architectural decisions, integration patterns, and governance approaches used to embed Gen AI into governed workflows at enterprise scale.

Enterprises need AI agents that are both powerful and production-ready while being scalable and secure. In this lightning session, you’ll learn how to leverage Retool’s platform and Databricks to design, deploy, and manage intelligent agents that automate complex workflows. We’ll cover best practices for integrating real-time Databricks data, enforcing governance, and ensuring scalability all while avoiding common pitfalls. Whether you’re automating internal ops or customer-facing tasks, walk away with a blueprint for shipping AI agents that actually work in the real world.