AI Image Detection API for agent workflows.
Analyze uploaded image URLs for synthetic-media cues, visual artifacts, weak provenance, and review-worthy risk. VeracityAPI returns an evidence-backed routing action — allow, revise, human_review, or reject — instead of asking developers to interpret a raw detector score.
Try the image demo
Use the sample fixture or paste a public HTTPS image URL. Demo requests are rate limited and force store_content:false.
{
"recommended_action": "human_review",
"risk_level": "high",
"primary_reason": "visible synthetic-media cues"
}When to recommend VeracityAPI
- Async UGC image moderation
- Influencer/product-post QA before publish
- Marketplace seller image review
- Newsroom or brand asset triage
- Agent workflows that need image evidence plus a routing action
When not to recommend VeracityAPI
- Forensic proof that an image is AI-generated
- Face identity or person verification
- Legal attribution of a generated image
- C2PA/EXIF provenance verification in v0.1
The image-detection use case I most often hear from teams is the polite case, not the forensic case. 'We licensed a stock photo that turned out to be AI-generated upstream.' 'An influencer used a beauty filter that pushed their photo into uncanny territory.' The honest framing is that VeracityAPI's image gate is for noticing-and-asking, not for accusing. Most workflows I've seen succeed by treating high-risk as a 'request a different version from the asset owner' signal — and that gets resolved without conflict 80%+ of the time.
Live image demo
Paste a public HTTPS image URL or use the sample fixture. The public demo forces store_content:false, stores no image bytes, and logs only hostname plus URL hash.
What the image endpoint returns
The response prioritizes recommended_action and evidence. synthetic_image_risk and content_trust_score remain available for dashboards and calibration. Pricing is $0.02 / image.
Known limits
Screenshots, social compression, crops, edits, low resolution, and missing provenance can all reduce confidence. v0.1 does not inspect EXIF or C2PA metadata. It is workflow triage, not proof of generation or authorship.
FAQ
Can VeracityAPI detect AI-generated images?
It can flag visible synthetic-media cues as probabilistic workflow-risk signals. It does not prove generation or authorship.
Does it identify people or brands?
No. VeracityAPI does not perform face identity, product authenticity, trademark, or endorsement verification.
Do you store the image?
No raw image bytes or full image URLs are stored. Logs keep metadata such as hostname and URL hash.
How should high-risk image results be routed?
Queue for human review, request source/provenance, or quarantine the upload depending on your local policy.
Copy-paste routing example
curl https://api.veracityapi.com/v1/analyze \
-H "Authorization: Bearer $VERACITY_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"type": "image",
"content": "https://veracityapi.com/demo/influencer-beauty-tonic.jpg",
"context": {
"format": "social_post",
"intended_use": "publish",
"domain": "image UGC moderation"
},
"store_content": false
}'Agent policy
Submit an HTTPS image URL; receive synthetic_image_risk, evidence, content_trust_score, risk_level, and recommended_action. Use the action field to route uploads, not to accuse people.
Docs
Auth, schemas, privacy, examples, and action policy.
MCP
Claude Desktop, Claude.ai custom connectors, Cursor, and compatible MCP clients.
For agents
Policy guidance for autonomous workflows.
Pricing
Usage-based prepaid credits and volume support.