Making spiders understood, not feared
We built Spider Identifier so that anyone — from the curious to the cautious — can recognise a spider in seconds and know exactly how to respond.
Bridging technology and biology
Most people meet a spider and feel one of two things: fascination or fear. Both usually come from the same place — not knowing what they're looking at. A field guide is slow, and a generic photo app rarely understands arachnids.
So we built a tool dedicated to one job. Computer vision isolates the spider, machine learning matches its features against thousands of labelled images, and real arachnology sharpens the result — all in under three seconds, on any device.
The goal isn't just a name. It's the confidence to know whether the spider in your garage is a harmless house spider or one worth keeping your distance from — and the knowledge to appreciate the remarkable animals most of them are.
Principles behind every result
Safety first
Every identification carries a clear venom-risk indicator and honest guidance — never false confidence.
Grounded in science
Predictions are refined with real arachnology: eye patterns, leg stance, habitat and web type.
Accessible to all
No app, no expertise and no cost to try. If you have a photo, you can identify a spider.
Honest about limits
We show confidence scores and flag uncertainty, because a trustworthy tool admits what it can't see.
Arachnologists meet engineers
A small team obsessed with getting spider identification right — scientifically and responsibly.
Dr. Elena Marsh
Lead Arachnologist
Two decades studying spider taxonomy and venom, now translating that expertise into models anyone can use.
Marcus Webb
Field Naturalist
Wildlife photographer and educator who has documented spiders on five continents.
Priya Nair
Computer Vision Lead
Builds the detection and classification pipeline that turns a single photo into a confident match.