Unlocking real-time geospatial intelligence with Elastic

Geospatial data volumes have exploded in recent years. Technologies like GPS feeds, satellite imagery, sensor networks, drone telemetry, AIS vessel tracking, and Internet of Things (IoT) endpoints mean that data now arrives continuously from many sources and at high speed. As a result, agencies are now dealing with a live feed of the world, rather than only a snapshot.

However, most geospatial stacks were built for a different era. Traditional geographic information system (GIS) tools provide powerful spatial analysis and visualization capabilities but are often constrained by underlying legacy architecture. As a result, it can be difficult to combine and correlate spatial data with high-volume telemetry data like logs, metrics, text documents, or security events, let alone ingest millions of data points per second, analyze them in real time, and surface answers in time to act.

The data exists, yet the intelligence doesn't move fast enough. With tool sprawl and legacy systems, too many analysts spend time wiring together incompatible systems. Relevant insights arrive after the moment has already passed. Because these tools require specialized GIS expertise to operate, that intelligence stays locked behind a small group of people rather than reaching the operators, commanders, and decision-makers who need it. 

According to John Castorani, who leads Elastic’s partnership with the US Special Operations Forces, most mission problems come down to two questions:

• Where is it happening?

• What does that information actually mean?

Conventional GIS tools answer the first question but struggle with the second.

“At its core, geospatial analysis is a search problem,” Castorani explains.

When you treat location like any other search parameter, such as a timestamp or a keyword, you unlock the ability to analyze millions of data points in mere milliseconds. You gain the ability to search the physical world in real time.

Elastic treats location as a first-class data type alongside text, numbers, dates, IP fields, security events, and logs. Coordinates, polygons, bounding boxes, and spatial relationships can all be queried with the same performance and flexibility as any other data. Data flows in through Logstash at high velocity and volume, stored and indexed for instant retrieval. That means analysts can ask questions like “what vessels crossed this corridor in the last six hours?” or “which assets are within kilometers of this incident?” and get answers immediately.

Elastic augments and enhances traditional GIS tools scaling back end data, providing first phase triage of massive datasets and exposing findings through open APIs for visualization and deeper analysis. Spatial data doesn’t have to be siloed in a specialized datastore. It can live alongside an organization’s other operational data, enabling richer context and more complete answers. 

Breaking down these silos also lowers the barrier for who can manage intelligence. “With natural language, you don’t have to learn how the system works or write complex queries — you can just ask questions and get answers,” says Peter Steenberge, GenAI Search Specialist at Elastic.

In time-sensitive environments, people who need answers aren’t necessarily the ones who know how to run complex spatial queries. With Elastic, less technical users can simply ask questions in natural language and instantly access insights across geospatial and telemetry data without requiring deep technical expertise or training.

Organizations like Blacksky — which monitors the globe across space, air, ground, internet, and sensor feeds — already rely on Elastic’s fast ingest, analysis, and search to correlate data from disparate sources and identify patterns or anomalies. That same architecture can be applied to challenges facing defense, law enforcement, and emergency response agencies. 

Real-time geospatial intelligence helps address inefficiencies across these environments:

• Law enforcement operations centers managing multiple simultaneous incidents need to know which units are closest to an operational situation, whether there is overlap with areas flagged for other activity, and how to allocate resources across a shifting picture. In these situations, data must be accessed in minutes, not hours.

• Emergency response teams operating during a large-scale natural disaster need live visibility into which areas are accessible, where resources are concentrated, and how conditions are evolving across a wide geography as the event unfolds.

• Critical infrastructure operators monitoring a distributed network need to trigger an alert the moment an anomaly appears, not after an analyst cycles through the data during their next scheduled review.

In each of these cases, the underlying requirement is the same: to ingest high-velocity, multisource geospatial data and convert it into something actionable before the window closes.

Maps will always play an integral part in geospatial tools. But the organizations that will operate most effectively in complex, fast-moving environments are the ones that treat location data as an active layer of operational intelligence. 

Elastic brings search, analytics, and AI together in a single platform built to handle the scale and speed that modern geospatial workflows demand — deployable across edge devices, on-premises servers, air-gapped environments, and cloud infrastructure without requiring teams to move or duplicate their data. 

The result is a system where maps help you understand what’s happening, anticipate what comes next, and take action before the situation changes. 

Ready to see it in action? Watch our webinar on turning geospatial data into real-time action.