Memory, State, and Knowledge Management: Powering Long-Running AI Systems

Stateless models are powerful but limited. True enterprise AI requires systems that can remember, adapt, and reason across time. This panel will explore how organizations are building memory and state management layers to make AI contextual, auditable, and persistent. Panelists will dive into vector databases, knowledge graphs, feature stores, metadata systems, and hybrid approaches that underpin everything from customer-facing chatbots to predictive analytics engines. Expect discussion of trade-offs in scalability, cost, and latency, as well as how leaders are weaving together structured enterprise data with unstructured knowledge to support long-horizon use cases. Attendees will walk away with a clear view of the state-of-the-art tools and strategies for turning raw data into durable knowledge that drives competitive advantage.