Tayanch tells real photos, video and audio from AI-generated ones — and says so honestly when it isn't sure. One API call.
Status is read live from the server, so the page never claims more than the API delivers.
Detection is probabilistic. A detector that only says “real” or “fake” will eventually accuse a genuine photo. Tayanch has a third answer.
Consistent sensor noise, optics, and compression history — the fingerprint of a camera. Returned as "verdict": "real" with the confidence behind it.
Heavily re-compressed, screenshotted, or genuinely ambiguous. Instead of guessing, the API says so and lets you route the file to human review.
Missing camera physics, a reconstruction error that fits a generator, an embedding off the real-photo manifold. Returned as "verdict": "ai".
Numbers from the August 2026 recalibration (14 held-out generator families; 800 real photos from sources never used in training) and the September 2026 live-API bench (112 fresh files). Content Credentials (C2PA) and generator markers are read before any pixel is scored; when the signal is ambiguous, Tayanch says "uncertain".
# one call, one verdict curl -X POST "$TAYANCH_API/analyze" \ -H "X-API-Key: $TAYANCH_KEY" \ -F "image=@photo.jpg" # → 200 OK { "verdict": "real", "label": "Real", "confidence": 96.4, "p_ai": 0.018 }
REST over HTTPS, JSON in and out. Send a file, or POST a link to /analyze/url and the server fetches the media itself. The base URL and your key are on the API page. Read the API page ›
One calibrated operating point, tuned for near-zero false accusation; custom thresholds per deployment on request.
Drop a file in the demo, or create a free API key — 100 checks, no card required.
