Charles River Analytics Supports DARPA Insight Program

Initiative Aims to Improve Intelligence, Surveillance, and Reconnaissance on the Battlefield

Charles River Analytics, a developer of intelligent systems solutions, won a follow-on contract valued over $1.25 million to support Insight, a Defense Advanced Research Projects Agency (DARPA) Information Innovation Office (I2O) initiative to improve intelligence, surveillance, and reconnaissance (ISR). Insight intends to bring real-time, integrated, multi-source intelligence to the battlefield by consolidating and automating data processing for intelligence analysts, who currently analyze data from multiple sources using manual processes too time consuming and inefficient for today’s time-sensitive missions. In contrast, Insight seeks to fuse data from all available sources, including multiple platforms and sensors, into a comprehensive operating picture, use algorithms to discover and predict possible threats, and allow analysts to develop and share actionable intelligence in real-time.

As part of the Insight team led by BAE Systems, Charles River Analytics plans to support the design and development of the Insight User Experience. The team plans to collaborate to mature the Insight system by integrating information from additional sources, such as space, air, sea, and ground sensors; human intelligence; and information repositories and networks. Insight also plans to support other mission domains, such as mobile missile hunts, counterinsurgency, wide-area security, and integrated air defense systems.


An intelligence analyst works with Insight

The Insight initiative has given us an excellent opportunity to blend our sound human factors design principles with highly complex computational systems,” said Dr. Jonathan Pfautz, Vice President, Cognitive Systems. “We are excited to continue with the program to mature and extend Insight’s capabilities using our world-class software and systems engineering skills.”

Charles River is a recognized leader in the design, development, and evaluation of human-machine interfaces for a wide range of decision-support systems.

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