Places

Validate Place

Validate if a place exists and has a digital footprint using AI-powered web search and analysis.

Given a natural language query like “Starbucks Market and 8th st san francisco”, this endpoint performs comprehensive analysis to determine:

Digital Footprint Analysis:

Entity Type Classification:

Determines if the query represents a place, address only, person name, geographic area, or other entity type

Place Definition:

Identifies the type of place: physical storefront, residential, temporary event, digital-only business (e.g., ghost kitchens, eCommerce), etc.

Place Reality - Location Match Granularity:

house_number: Evidence found at exact address including street number (e.g., “123 Main St”)
nearby: Evidence found on same street but without exact house number (e.g., “Main St” in same city)
broad: Evidence found in general area/city but at different street or only partial address match
none: Unable to match the place to any specific location

Input sensitivity: The achievable location_match_granularity depends on how specific the input is.

Example — nearby: Input “Starbucks 123 main st san francisco” → location_match_granularity: nearby. Web sources may resolve this to an actual Starbucks at “5075 Main St, San Francisco”. We will still confirm the existence of “Starbucks, San Francisco” as a place: it DOES exist, it has HIGH internet presence, and it DOES have a storefront.
Example — broad: Input “Starbucks San Francisco” (name + city only) → location_match_granularity: broad. We can confirm the brand exists in the city, but without a specific street/house number from the input, the match stays broad.

Important Notes:

This endpoint validates place existence and digital presence, but does NOT determine if a place is currently open or closed
For open/closed status verification, use the closed_permanently enrichment via the /enrich endpoint