Cold-start natural-language search often lacks both real queries and relevance labels. Airbnb's CASTLE jointly generates synthetic queries and labels from de-identified booking sessions. Its queries matched real guest query patterns much better than baselines, and human reviewers agreed with its relevance labels >90% of the time. Carefully governed behavioral data can bootstrap search training before meaningful traffic exists.