In the AI era, “looks authentic” is a weak review standard. A RealityProof receipt lets teams inspect capture source, fresh-request status, and file match. It adds provenance—not a verdict about the scene.
realityproof.app
A proof link can stay with a return, claim, or property record. Teams can review available source, freshness, and file-match checks in the browser—or read them through the Verify API—then apply their own policy and judgment.
@C2PA_Signer Delivery survival and signer trust are separate checks: a preserved manifest can still chain to an unknown issuer, while a stripped one leaves origin unverified.
Start a provenance pilot with one narrow workflow: one evidence request, one capture receipt, and one reviewer decision.
That keeps the test focused on inspectable capture history—without pretending provenance makes the final call.
realityproof.app
@NankyaJoan71 That last point is the operational constraint: better models do not repair missing evidence context. Claims teams still need inspectable inputs, explicit checks, and human judgment—not another opaque score.
@ReadOmniscient Exactly: a valid capture signature can establish device/source and pixel integrity, not what was in front of the lens. Good review UX should surface that boundary instead of collapsing provenance into a “real” badge.
Evidence review shouldn’t require making evidence public.
A reviewer can compare a file with its RealityProof receipt in the browser. The original stays on reviewer’s device; the receipt shows source, freshness, and file match.
realityproof.app
@spaisee_com That distinction matters. Provenance can verify a signed history or origin claim; it cannot prove the depicted scene was complete, unstaged, or truthfully described. Interfaces should show both the checks and their limits.
@cse_cst A useful implementation detail is to expose the individual provenance checks, not just a single trust badge. Source, integrity, and freshness answer different questions—and none replaces judgment about the scene or claim.
@FlocAmbergang For high-stakes use, “AI-generated probability” is usually the wrong threshold. Prefer verifiable provenance from capture/signing, treat missing provenance as unknown—not fake—and keep human review for the claim itself.
An image is easy to inspect. Its capture history isn’t.
RealityProof adds a reviewable receipt: capture source, fresh-session status, and file match—while the original evidence stays private by default.
realityproof.app
We shipped 🚀
Reality Proof: 3D Scanner is now available on the App Store.
Our first step toward making physical reality easy to capture, preserve, and verify in 3D.
Built for iPhone. More updates soon.
apps.apple.com/us/app/reality…
iOS app progress update 👇
Here’s what the app currently looks like while we keep building:
• Simple capture modes (Room + Object)
• Verified scans with on-device checks + L2 KMS co-signature
• Direct access to the Public Verify API + version transparency
Version 1.0 is live for testing. We’re focused on making real-world capture smooth and the resulting proofs easy to verify anywhere.
Still iterating. What feature would you want to see added next?
Link in bio to test.
Capture. Verify. Prove.
#ProofOfReality
AI makes generating content cheaper every day.
Reality is becoming the scarce resource.
The next generation of marketplaces, insurers, RWAs, and autonomous agents won't just consume media.
They'll need to verify it.
Not:
"Does this image look real?"
But:
"Is there a proof that this capture existed in the physical world?"
That's the problem we're solving.
We are heads-down on the builder layer: public API docs, OpenAPI clients, SDK shape, and an MCP path for agents that need to verify physical-world claims.
One proof id should be usable by any app, marketplace, protocol, or agent.
We built Proof of Reality: a public verification layer for real-world scans.
A capture gets a verifyId and canonical bundleHash.
Any app can check it through a public API. Raw files, GPS, nonce payloads, and app-key details stay private unless the user opts in.
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