A tech company needed a better way to identify passive candidates, not just active applicants. The team lacked enough context beyond resumes to predict fit and prioritize who would respond. They also needed to understand relationship connections so outreach could follow warm paths where trust already existed. The company implemented an AI talent intelligence approach built on expert-labeled data and relationship intelligence. It used relationship signals to map how candidates were connected and to prioritize in-network, warm-path prospects. The solution converted unstructured career data into labeled attributes and success signals to add context for sourcing and evaluation. The approach accelerated sourcing speed and improved early-funnel engagement. It delivered 24x faster sourcing. It also produced 2–8x more interested candidates and an 80% interview advancement rate.