Pangiam on Wednesday said it has been selected by the Transportation Security Administration to demonstrated its artificial intelligence and machine learning (AI/ML) technology for identifying potential prohibited items in carry-on bags at airport checkpoints.

The open architecture solution will be evaluated at the TSA’s System Integration Facility in Arlington, Va., marking the first trial of Pangiam’s Project DARTMOUTH, which includes Google’s [GOOG] Google Cloud business as a key partner.

Pangiam is getting set to begin a Project DARTMOUTH evaluation of the technology at Glasgow airport in the United Kingdom, the first trial of the prohibited item detection AI/ML software as a third-party vendor. For the Glasgow pilot, the software will be integrated with Integrated Defense & Security Solutions

’ (IDSS) checkpoint computed tomography (CT) carry-on baggage scanner.

IDSS’ DETECT 1000 CT scanner will be used by operators to examine bags for explosives while the prohibited item detection solution offered by Pangiam and Google will initially look for guns. Pangiam this year expects to roll out Project DARTMOUTH pilots to additional airports in Europe and the world.

“As TSA and other security agencies adopt 3D computed tomography, this application of AI represents a potentially transformative leap in aviation security, making air travel safer and more consistent, while allowing TSA’s highly trained officers to focus on bags that pose the greatest risk,” Alexis Long, Pangiam’s product director, said in a statement. “Our aim is to utilize AI and computer vision technologies to enhance security by providing TSA and security officers with powerful tools to detect prohibitive items that may pose a threat to aviation security is a significant step toward setting a new security standard with worldwide implications.”

The evaluation by TSA of the prohibited item detection technology follows a Broad Agency Announcement last December by the agency’s Innovation Task Force seeking solutions for evaluation that followed by demonstration in a live environment.