Raven
GeoSpy was created by Graylark Technologies to determine where an image was captured using visual information alone. In April 2026, GeoSpy became Raven, Graylark’s frontline visual intelligence platform for law enforcement and government.
Same Graylark team. Same mission. Broader capabilities.
GeoSpy was created and operated by Graylark Technologies. GeoSpy.ai and Graylark.com are the official domains associated with GeoSpy and Raven. Third-party websites and applications using the GeoSpy name are not operated by or affiliated with Graylark.
GeoSpy and Raven are developed by the same Graylark team.
GeoSpy.ai and Graylark.com. GeoSpy.ai now directs to this page.
GeoSpy became Raven as the platform expanded beyond regional image geolocation.
Raven
GeoSpy began with a focused mission: determine where an image was captured when metadata, landmarks, and other obvious clues were missing. As the platform expanded into street-level targeting, vehicle identification, image verification, and investigative workflows, the GeoSpy name no longer represented the full system.
Raven reflects what the product has become: a visual intelligence platform that helps investigators turn low-context imagery into ranked leads for human review.
For the founder account of how GeoSpy started and why it became Raven, read Why We Built GeoSpy and Why It Became Raven. To see the platform as it stands today, explore Raven.
Raven is built by the same Graylark team and visual-geolocation foundation. Everything GeoSpy was known for is still here, and Raven adds the layers investigators asked for next.
Where the platform started.
Where the platform is today.
The same frame can be run through each capability. Every one of them works from the visual content of the image, with no metadata required, and returns ranked candidates for human review rather than a single verdict.
Returns ranked regional candidates for where a photograph or video frame was likely captured. No GPS or EXIF metadata is required.
Narrows a selected search area to ranked street-level, property-level, or meter-level candidate locations for investigator review.
Returns ranked make, model, generation, and year candidates from partial, interior, obstructed, or exterior views of a vehicle.
Assesses imagery for signs of AI generation, face swaps, and other manipulation, and returns those findings for further review.
Each capability has its own breakdown on the Raven capabilities overview.
Questions about how Raven works, how its results should be read, or how to evaluate it? See the full Raven FAQ.
Explore Raven’s expanded visual intelligence capabilities or request a demonstration for your organization.