Traditional websites rely on structured data, but AI agents need richer venue information. Natural Language Web (NLWeb) lets venues describe their personality and ambiance through descriptive text, capturing experiential qualities beyond amenities. Instead of filtering by simple criteria, super-agents can search for nuanced descriptions like "good for working but not corporate" and receive meaningful results. Venues communicate personality with phrases like "bustling but not chaotic." This requires a shift from amenity lists to atmospheric descriptions that help AI agents understand emotional fit. The challenge is maintaining accuracy while enabling nuanced matching. NLWeb leverages natural language processing to match guest preferences with venue descriptions, understanding synonyms and context. Early implementations focus on obvious personality traits, but are evolving toward subtle emotional and atmospheric matching that improves guest satisfaction through better venue-preference alignment, leading to more coordinated bookings and agent-ready venues.
