Multi-INT Analytics for Pattern Learning & Exploitation (MAPLE)

Multi-INT Analytics for Pattern Learning & Exploitation (MAPLE) uses advanced machine-learning technology to analyze real-time or archived data streams to rule out routine background activities and focus watch-stander attention on infrequent anomalies.

MAPLE adapts quickly to local conditions and traffic patterns, using a non-statistical approach that can derive information from only one example. MAPLE has been applied to maritime shipping and port surveillance domains, as well as to border security and protection of deployed U.S. forces.