Clinical trials continue to face increasing operational complexity, fragmented workflows, and growing pressure to accelerate timelines without compromising governance or quality. Project Loom, led by i-Cubed at DCRI in collaboration with Maxis AI, explored how a supervised AI Workforce can help orchestrate regulated clinical trial workflows with greater speed, consistency, and operational scalability.

Download the case study to explore how Project Loom leveraged a supervised AI Workforce to orchestrate complex clinical trial workflows:

• How Project Loom reduced execution timelines from 6–9 months to 182 hours.
• How supervised AI agents orchestrated end-to-end clinical workflows.
• How governance, audit traceability, and human oversight were maintained.
• How operational bottlenecks across startup, data, and reporting workflows were addressed.
• How an AI Workforce model can improve throughput without proportional headcount scaling.