Events and Webinars
Conferences we’re attending, booths we’re running, and webinars we’re hosting on agentic data engineering. Register for what’s coming up, or catch the replay of a session you missed.
Upcoming
Webinar: When AI Agents Build Trusted, Production Pipelines
Most organizations run on data operations in the background, continuously producing critical data. Waiting for engineers to build and maintain pipelines doesn't scale and creates brittle dependencies and inconsistencies. Naively deploying AI to take over processing isn't the solution, as it can result in hallucinated insights, untraceable lineage and pipelines that cost 10x more to operate. In this session, Brian Frutchey, CTO of Clear Fracture, shows how appropriately designed agentic data engineering changes the equation. You'll see how autonomous AI agents can design, build, validate and govern production-grade data pipelines while keeping every decision auditable, every transformation explainable and every cost dramatically lower than chatbot-style AI or manual approaches. **What we'll cover** - Why chatbot-style AI fails at scale - How agentic data engineering acts as a force multiplier, with real-world metrics showing a 5-10x reduction in pipeline development effort and time - Maintaining compliance with full auditability and oversight - A live demonstration of an agent building a production data pipeline
Federal AI Forum: What's Working in AI? Pilots and Use Cases Panel
The gap between an AI demo and a production system is where most projects quietly die. It's not a model problem. It is a data, trust, cost, and repeatability problem. Agencies have schema drift, undocumented handling rules, approval chains that exist only in someone's head, and pipelines built for a source that changed six months ago. The AI sits on top of all of that and gets blamed when it fails. Our CTO Brian Frutchey will be on stage at the GovCIO Media & Research Federal AI Forum on August 13 in Reston, VA talking about exactly this. His session is a lightning round with federal AI leaders sharing what is actually working as agencies move from early experiments into real operations. What breaks at scale. What governance gaps surface late. What the teams that ship have in common. If you’re working on AI adoption inside a federal agency (or supporting one), this is the room for the honest conversations.