For most organizations, the biggest hurdle to leveraging Artificial Intelligence isn’t the models—it’s the data. Spatial data, from complex vector layers to planetary-scale imagery, is notoriously difficult to structure, process, and make accessible for AI agents and machine learning pipelines.

Join Wherobots and Felt as we explore how to bridge the gap between the physical world and AI. We will demonstrate how the Wherobots Spatial Intelligence Cloud transforms unstructured geospatial data into a “Spatial Data Lakehouse” architecture that is purpose-built for AI. Then, see how Felt provides the collaborative canvas to visualize these AI-driven insights in near real-time.

In this session, we’ll cover:

  • Structuring for Intelligence: How to move beyond static files to an AI-ready spatial data lakehouse using Apache Sedona and the Wherobots engine.
  • The New “Code-to-Map” SDK: A look at the native integration that allows data scientists to process AI-ready datasets in Wherobots and push them instantly to Felt for human-in-the-loop validation.
  • Chat with Your Data: A live demo of the Wherobots MCP (Model Context Protocol) server, showing how knowledge workers can use natural language to query complex spatial data and generate maps.
  • From Pixels to Predictions: Automating the transition from raw raster imagery to AI-ready features that drive predictive models in Agritech, Insurance, and Logistics.

Stop fighting your data and start fueling your AI. Learn how Wherobots and Felt are making the physical world queryable, visual, and AI-ready.