Suicide is the leading cause of death in U.S. jails, occurring almost four times more often than in the general population. In-custody deaths result in unnecessary loss of life, significant potential liability, and major disruption within facilities. This poster evaluates the use of an artificial intelligence (AI) assessment model using video, speech pattern, and other data-driven indicators in identification and prioritization of those at risk for suicidal ideation.