This webinar explores how to build and use Agentic Geospatial systems for tasks like route optimization, site selection, and spatial analysis. It covers two key use cases—warehouse placement and site performance analysis—and includes a technical demo using LangChain or Snowflake to integrate geospatial AI into enterprise workflows.

Fragmented and siloed data is a critical barrier to confident decision-making across industries like insurance, retail, and real estate. This webinar from Korem explores how a modern, graph-based data architecture—powered by GraphQL—can unify geospatial datasets to enhance data integrity, improve risk assessment, and accelerate operational insight. Attendees will discover how connected, high-quality data drives better outcomes and see real-world examples of how organizations are unlocking value through smarter geospatial data integration.

Geo data can be the key to being more competitive and differentiating yourself from the competition. From site analysis applications to demographic evaluations, data leads to faster decision-making and increased ROI. Enriching your Snowflake environment through accurate data should be one of your main priorities to gain the upper hand on the competition.

In this workshop you will learn how GIS traffic data solutions can maxime your ROI, how to leverage data for site selection in high density areas and more!

Location technology and data are now key to many data-driven processes in various industries and is now proven to be a key differentiator in building an optimal EV charging location strategy. Learn how to leverage location analytics for developing a future proof EV infrastructure strategy to reduce the total cost of ownership.

The arrival of alternative energy vehicles represents the biggest disruption to the fuel market in many years. The main challenge for today’s charging network companies and real estate industry is how to properly develop their EV strategy, where to start, and what tools and data are available to help them in their decision-making.

For years, the retail industry has relied on Annual Average Daily Traffic (AADT), but that data source has lived passed its usefulness. While it may be sufficient for site selection, it is not for operational analytics. The new standard for today and the future is using Detailed Historical Traffic (DHT). It leverages a more timely, more accurate, and higher frequency source: probe data.

The arrival of alternative energy vehicles represents the biggest disruption to the refueling market in many years. Location technology and data are now key to many data-driven processes in various industries and is now proven to be a key differentiator in building an optimal EV strategy.

In the past few years, we have seen a change in how people and goods move around urban and suburban areas. Cities needs to find innovative ways to improve congestion, improve life of citizens and optimize the transport of goods. A better processing, collection and analysis of real-time location-based data may just be the solution.

Traditionally, retailers have leveraged demographic and socio-economic indicators to analyze and predict store sales. While this was adequate five or ten years ago, this approach no longer offers enough substantive information for sales projections, pricing, merchandizing or competitive intelligence.

The need for immediate access to traffic data is increasing as the demand for narrower time windows and to improve the customer experience is required by fleet managers for both long-haul and local delivery.

Encouraging positive improvements in driving behavior result in safer, eco-friendly trips, thus helping organizations achieve safety and sustainability goals.