— For enthusiasts & OSINT
Verify before you amplify.
Zoomed-in fingers and “look at the eyes” threads don't scale — and they're wrong more than anyone admits. Score the image with the same calibrated pipeline forensic labs use, in the time it takes to quote-post.
— Use cases
Where a calibrated score beats squinting
Breaking news
Viral image triage
A “photo from the scene” is spreading fast. Get a threshold-calibrated verdict before it enters your thread, your server, or your notes.
Accounts
Avatars & personas
Suspected bot networks love generated portraits. Batch-check profile pictures over the API and rank by primary score.
Communities
Fact-check receipts
Attach the JSON report — hashes, thresholds, limits — instead of a hunch. Your correction carries its own evidence.
Marketplaces
Listings & rentals
Too-perfect product shots and apartment photos that don't exist. One check before you pay a deposit.
Archives
Datasets & collections
Sweep an image folder through the batch endpoint and quarantine what flags at your chosen standard.
Discourse
Settling the argument
“It's obviously AI” vs “it's obviously real” — replace both with a number, its threshold, and its known error rate.
— Why it works on real posts
Calibrated for the gutter of the internet
By the time an image reaches you it's been re-encoded by WhatsApp, screenshotted on a phone, and re-uploaded twice. Detectors that shine on pristine files fall apart there — so our benchmark degrades every test image through those exact chains, and verdicts are calibrated per condition.
The journey your evidence took
originalgenerator output or camera filewhatsappmessenger re-encode · 1600px dual passscreenshotphone screenshot · rescale + brightness shiftsocial_chainwhat you finally saved — and what we calibrate for
Detection power under social_chain is printed on every report — 55% at the standard cap on our current run. When the honest number is modest, you deserve to know it.
— Score literacy
Read the score like an analyst, not a fan
The primary score lands between 0 (confident real) and 1 (confident AI). What matters is where it sits relative to the thresholds calibrated for your image's condition — shown here for the social-chain condition.
Below both thresholds. Not cleared — not flagged. Say “no detection at a 5% false-positive standard”, not “verified real”.
Above the standard threshold for this condition, below strict. Solid triage signal — worth a provenance dig before you amplify.
Above the strict threshold calibrated to ≤1% false positives on every real source. As strong as a single-image signal honestly gets.
— Scriptable
Your tooling, your pipeline
Everything the web app does is one authenticated POST. Export JSON, pipe it into your sheets, bots, and notebooks. Credits start at $9 for 10 images — no subscription required.
curl -s -X POST https://api.vestigeforensics.com/v1/analyze \
-H "Authorization: Bearer dl_live_9x2…" \
-F "image=@suspicious.jpg" | jq '.decision.verdict'Check the image before you quote-post it
One free analysis with an account, then $9 for ten more. The report is yours to attach, cite, or delete.