Whereisthis
Whereisthis identifies photo locations using EXIF GPS extraction and AI visual analysis on an interactive map. Free and privacy-first.
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What is Whereisthis?
Whereisthis (whereisthis.place) is a free AI geolocation tool that identifies where a photo was taken. It extracts embedded GPS/EXIF metadata instantly in the browser, and when metadata is missing, uses AI visual analysis to read architecture, signage, and terrain, then geocodes results on an interactive map with ranked predictions. Supports JPG, PNG, WebP, and iPhone HEIC formats. Privacy-first, built for places not people.
Whereisthis pricing
Pricing model: Freemium
Free EXIF GPS extraction in-browser; full pricing for AI analysis tier not specified
Whereisthis pros
- Free EXIF GPS extraction with instant in-browser processing — no server uploads
- Privacy-first design: photos are never stored on servers
- Covers 190+ countries with AI visual analysis for GPS-free images
- Supports multiple formats including iPhone HEIC
- Returns 5 ranked predictions with confidence scores and interactive satellite map
Whereisthis cons
- Accuracy varies significantly by scene type — urban streets 55–90%, rural/indoor scenes less reliable
- Pricing model for full AI analysis beyond EXIF is not clearly specified
- No batch processing or bulk analysis mentioned for commercial/research use
Frequently asked questions about Whereisthis
What happens to my photos after I upload them?
Photos are never stored on servers. EXIF data is processed locally in your browser for GPS-based results.
How does it work if my photo doesn't have GPS metadata?
The AI reads visual clues like signage language, architecture, roof styles, and road markings to rank 5 location predictions with confidence scores.
What file formats are supported?
JPG, PNG, WebP, and iPhone HEIC formats are supported.
How accurate is the geolocation?
Typical top-prediction confidence ranges from 55–90% for urban scenes. Accuracy depends on scene type — distinctive landmarks or unique signage push confidence higher, while generic suburban streets produce wider prediction spreads.