Ukrainian drone pilots have been trained so far to operate an "army of drones" against Russia's invading forces.

$750 M

Expected spending by the U.S. Army to develop light robotic combat vehic

19 TB/hr

The amount of raw data that can be generated by sensors on a single driverless vehicle.

The war in Ukraine is a case study of how rapidly the character of war is evolving, with attack and surveillance drones of various sophistication having come to dominate the battlespace.

It is incumbent on the Defense Department (DOD) to implement capabilities at the network edge that allow our armed forces to operate resiliently in remote environments against a wide range of manned and unmanned threats.

“Warfare is changing very fast. This threat right here, this current threat with respect to UAS, it’s the pace of your phone changing.”

Col. Moseph Sauda
Director, Joint C-sUAS University

AI and autonomy are potent tools revolutionizing battle management workflows today and forevermore. Battle management systems integrated with and boosted by artificial intelligence technology are:

  • Accelerating task execution and increasing the battle manager’s operational scope.
  • Unlocking new opportunities to automate processes like target identification and signals intelligence.
  • Enabling streamlined, operator-reviewed recommendations instead of requiring multiple personnel inputs during compressed timelines.

How AI Enhances
Battle Management

Decision Dominance

Reduce cognitive load and enhance domain awareness by making sense of disparate data forms and classifications.

  • Enhanced domain awareness across echelons in shortened timescales.
  • Consolidated risk monitoring.
  • Active alerts for suspicious activity.
Multi-INT Analysis

Leveraging AI in battle management networks provides opportunities to enhance existing systems while operating across

  • Textual data sources in multiple languages.
  • Multi-physics sensor networks.
  • Multi-domain manned and unmanned platforms.
Compounding AI Effects

Opportunize all data forms to achieve meaningful anomaly detection using compounding effects of full-spectrum AI solutions.

  • Distributed anomaly detection.
  • Accumulative impact of orchestrated AI classes across varied data sets.

Solving The Problem


SparkCognition Government Systems Multi-Domain Awareness Advisor leverages all data forms to provide meaningful anomaly detection using compounding effects of full-spectrum AI solutions to deliver real-time insights and course of action recommendations to the appropriate command echelons in the cloud or at the edge.