AI provenance2 min read

AI image provenance: records, watermarks and C2PA

How to keep a record of where an AI image came from, and where your records, invisible watermarks and C2PA Content Credentials each help.

In this guide

Start with what you know

Provenance means an image’s recorded history: where it came from and how it changed. If your service generates images, save the model version, creation time and later edits before publishing.

Give each tool a clear job

Your records
Keep the details of creation, edits and delivery in your system. Control who can change them.
Invisible watermarks
Add a signal that a compatible detector can read to help identify the image or find its record.
Content Credentials
Attach digitally signed statements about creation and edits, using the C2PA standard. Readers can check who signed them and whether they changed.

Plan for lost metadata

Sharing tools can strip information attached to a file. Some Content Credentials systems use watermarks and image fingerprints to find a saved credential again. A fingerprint recognizes visual content; a watermark adds a signal.

Etchv links a detected watermark to your records. It does not issue C2PA credentials. Signed history needs a separate C2PA tool, and a valid credential doesn’t prove the pictured scene is true.

Connect the image before publishing

Create a reference
Use a unique reference for each record. Keep prompts and personal details in your own storage.
Watermark the final image
Finish your edits, send the image and reference to Etchv, then save the returned watermark ID with the record.
Publish and check
Share the verified output. Test any later resizing or compression, and keep the record available for future lookups.

Need to distinguish recipients? Give each delivery its own reference and link it to the original generation record.

Leave room for “unknown”

A known watermark connects to the history you saved. Show that history and its source. A missing mark or credential does not mean an image was made by a human.

Detectors recognize the systems they support. Etchv checks for its own watermarks; it cannot classify any image as AI-made. Altered files, missing records and other watermark systems can all leave the result unknown.

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