If you want to scare a Data Engineer with four words, ‘big data, high concurrency’ will probably do it. As data moved from the realm of BI reporting to being a customer-facing commodity, serving huge volumes of data to thousands of unforgiving app users is no small challenge. In this session, Connor Carreras will share (and demo!) how a major martech platform uses Firebolt to serve data about millions of websites to their worldwide customers with consistent millisecond response times. After this session, you will know how you can build low-latency data applications yourself. You’ll also have a deep understanding of what it takes for modern high-performance query engines to do well on these workloads.

Whether they’re part of a workflow or powering a user experience, AI agents often need to work on your data at interactive speeds. Because of this, they demand more from data systems than traditional analytics workloads. Low latency is no longer a luxury, and handling concurrency is essential if you want an agent to scale with a growing platform. But with great access comes great risk: safeguards and strict permission models are critical. This talk will explore the principles and patterns for building responsive, reliable data infrastructure that agents can trust and users can depend on.

Tech talk as part of the AI meetup in Paris. Topics include AI, GenAI, LLMs and Agents.