Who
Gumnut detects people in your photos and identifies the same individual across your entire collection.
GUMNUT FOR ENTERPRISE
Automate your photo review and categorization
Whether you're moderating millions of user uploads or organizing a library you capture yourself, Gumnut is the intelligence layer that turns every photo into structured, queryable data — ready for your systems to act on.
Moderation pipelineLive · 12,480/hr
- IMG_4821.jpgProduct › Footwear › SneakersApproved
- IMG_4822.jpgFlagged · policy violationFlagged
- IMG_4823.jpgLifestyle › Outdoor › BeachApproved
- IMG_4824.jpgReview queue · low confidenceRouted
Why teams choose Gumnut
Automated, customizable photo intelligence pipelines
Custom taxonomy
Categorize photos your way — not a vendor's generic schema. Define the labels and hierarchy your business actually uses.
Moderation at scale
Gumnut analyzes every upload — content, context, and policy signals — so your review systems can flag and route consistently, across millions of images.
Agent-native by design
No more switching between windows. Anything your team can do by hand, an agent can do too — through Gumnut's hosted MCP server.
The technology
Complete understanding of every photo
Gumnut reads each image the way a person would — and returns it as structured, queryable data.
What
Gumnut analyzes the content of every photo and knows what's in it — objects, scenes, text, and activity.
EXIF · DateTimeOriginal
July 14, 20234:32 PM GMT+2 · golden hour
When
Gumnut combines file information, capture metadata, and visual cues to pin down exactly when each photo was taken.
Where
Gumnut reverse-geocodes embedded GPS coordinates into readable, human places — and even when photos have no GPS, it infers the location from visual landmarks and context.
EXIF · Camera
iPhone 15 ProMain camera · 24 mm
ƒ/1.781/120 sISO 64
How
Gumnut surfaces the technical fingerprint of every photo — the camera, lens, and capture settings read straight from its EXIF data.
Bring photo intelligence to your workflow
Tell us about your taxonomy, your volume, and your stack. We'll show you what an automated pipeline looks like.