TRM Launches AI Practice to Bridge Gap in Asset Management

The new practice focuses on integrating predictive maintenance, automated work management, and intelligent troubleshooting into the systems firms already use. By connecting enterprise-wide AI strategies with the realities of operational uptime and throughput, TRM seeks to move intelligence out of the experimental phase and into practical, daily utility. Jordan Ortiz, Director of AI Strategy at TRM, noted that the goal is to weave data-driven insights into established processes while maintaining strict control over security and governance.

At the center of this initiative is OMNI AI Studio, a development platform designed to unify testing, training, and workflow automation. The tool supports tasks ranging from generating bills of materials to recommending specific maintenance actions based on failure codes and inspection requirements. For firms lacking a formal industrial AI framework, the practice offers advisory and architectural guidance to ensure new deployments align with existing infrastructure and long-term security needs. CEO Don Omura emphasized that the initiative is built on augmenting human expertise rather than replacing it, focusing on equipping personnel to act with greater confidence when managing critical assets.