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A hands-on workshop with AWS & Wherobots, plus a fireside chat with HERE Technologies
Note: that this event is at an AWS facility & as such AWS requires all attendees register via their registration page to attend. Please do so in addition to signing up on this luma by filling out this form: https://events.builder.aws.com/nNlEnR
Agenda
10:00am to 10:30am: Doors open & check-in
10:30am to 11:00am: Fireside chat: Precise answers from probabilistic AI
11:00am to 11:20am: Context Engine for Physical World Data : Vision & Mission
11:20am to 12:45pm: Hands-on workshop
12:45pm to 1:45pm: Lunch & networking
Fireside Chat: Precise Answers from Probabilistic AI
Ben Pruden, Head of Go-to-Market at Wherobots, & Herv Utheza, Senior Director, AI & Emerging Technologies at HERE Technologies, on what it takes for AI to give exact answers about the physical world.
Large language models are probabilistic. Ask the same question twice & you get two different ballpark answers. Questions about the physical world, like which properties sit inside a flood zone or how many people live within a wildfire hazard area, need exact, repeatable results. Ben & Herv discuss how AI agents get there by calling deterministic geospatial tools.
Vision & Mission at Wherobots: Giving Agents Context for the Physical World
Mo Sarwat, CEO of Wherobots will introduce the company & vision as the Context Engine for Physical World Data. He will introduce how Wherobots enables agents to reason deterministically on spatial data, & what that means for the next generation of agentic infrastructure & physical AI. Mo is one of the two original creators of Apache Sedona.
Workshop: Building a Geospatial Agentic AI Stack on AWS & Wherobots
Build an end-to-end agentic geospatial pipeline in a single day. Bring your laptop, leave with a working pattern for turning raw satellite imagery & weather data into interactive risk dashboards, driven by natural language at every stage.
This in-person workshop walks you through building an end-to-end geospatial AI pipeline. Raw satellite imagery & weather data go in, move through agentic data engineering & risk scoring, & come out as interactive map dashboards. You use natural language at every stage.
By the end of the workshop you will be able to:
Work with Amazon Kiro for AI coding to build & interact with Wherobots & AWS.
Use the Wherobots MCP server as an agentic interface for exploring & processing geospatial data catalogs
Build a medallion data pipeline (Bronze, Silver, Gold) using spatial SQL, raster zonal statistics, & KNN spatial joins on WherobotsDB with Apache Iceberg
Score physical assets for natural hazard risk using wildfire, flood, & severe weather data
Connect Aurora PostgreSQL as a live data source to MapLibre as a visualization layer, so maps stay current as the underlying data changes
Who Should Attend
Data engineers, ML engineers, & solutions architects working with physical-world data. Geospatial teams evaluating how agentic workflows layer onto existing GIS infrastructure.
Sponsors
This event is made possible by our sponsors, who keep the Data for AI community running.
About Wherobots
Wherobots is the AI Context Engine for physical world data, built by the original creators of Apache Sedona. An AWS Partner, the platform enables planetary-scale spatial compute & Earth intelligence, letting developers build & scale AI workflows on physical-world data using the SQL & Python they already know. Learn more at wherobots.com.
Datastrato is the original creator of Apache Gravitino, the open-source metadata lake that puts tables, models, & files under a single catalog, lineage graph, & access layer. They are building the open data fabric platform to accelerate trusted AI, & host the Data for AI community. More at datastrato.ai.
About 9Zero:
We're a members-only community of founders, investors, scientists, & innovators accelerating climate solutions through meaningful relationships. Apply to join at www.9Zero.com
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