Consent is now a legal posture
Children's biometric and image data sits squarely inside modern privacy law. A single missed consent isn't an oversight any more - it's a notifiable issue.
On-device photo consent screening
Know who’s in every photo before you publish.
FaceGate screens your photos against an enrolled consent list - entirely on the device - so schools and childcare centres can publish with confidence. No cloud. No third parties. No surprises.
- No cloud calls
- Runs on the phone
- Apache 2.0 model
01 / 05·Consent gate
Explicit opt-in before a single frame is scanned.
Slide 1 of 5: Consent gate. Explicit opt-in before a single frame is scanned.
- 100% on-device
- No cloud calls
- Apache 2.0 production model
- Full audit trail
- Material 3 design
Why this matters
Every photo a school publishes might contain someone who didn’t consent.
Manual review doesn't scale
A sports day or production can produce hundreds of photos in an afternoon. Eyeballing each one for non-consenting faces is slow, tiring, and error-prone.
Cloud tools are the wrong trade
Most off-the-shelf face recognition uploads photos to a vendor's servers. Using one means sending children's faces to a third party to solve a privacy problem.
The risk isn’t a bad photo getting through - it’s not knowing you let one through.
The solution
A phone app that screens photos against a consent list - before they go anywhere.
Stays on the phone
Faces never leave the device. No cloud. No third parties.
Consent-aware
Tag people as Include or Exclude. The app handles the rest.
Fast on a batch
Scans dozens of photos and gives you a verdict per image.
Publish-ready
Cover faces with a blur or emoji, export, done. Full audit trail.
Built so you can replace manual review with a structured, auditable workflow.
Try it
Flip a person’s status. Watch the photos re-classify.
Three illustrated photos, three enrolled people. Toggle Include ↔ Exclude and watch the verdict shift - the same rules the app applies on-device: any Exclude face → Unsafe; any unknown face → Review; otherwise Safe.
Toggling consent here changes the verdict only - not the photo. In the real app, redaction (a blur or emoji overlay) is a separate operator step after the verdict.
1 face
SafeWhy? All faces are on the consent list as Include.
2 faces
UnsafeWhy? Blake is Excluded and confidently matched.
3 faces
ReviewWhy? An unknown face was detected - flagged for human review.
Consent list
Illustrative. The same logic runs on your device with no network calls.
Alex
Blake
Casey- Not on list
Unknown
How it works
Same workflow you’d do by hand - just structured and fast.
1
Enrol
Add the people whose consent you're tracking. A few photos each is enough.
2
Scan
Point the app at a folder or take a photo. It detects and recognises every face.
3
Classify
Each photo lands in one of three buckets: Safe, Unsafe, or Review.
4
Publish
Cover non-consenting faces, export, post.
Every step runs locally on the phone - no internet required.
Compliance posture
Designed against modern Australian privacy law.
FaceGate is built against the Australian Privacy Principles and the WA Privacy and Responsible Information Sharing Act 2024. All biometric data stays on-device - no cloud upload, no cross-border transfer, no central store to breach. Every action is timestamped in the on-device audit log.
APP-alignedAuraFace v1 · Apache 2.0100% on-deviceFull audit trail
The internet
Nothing leaves your phone
Your phone
- 1. Photo
- 2. Detect
- 3. Match
- 4. Verdict
Your photo is checked right here on your phone. It’s never uploaded or sent to the internet.
Where it fits
Built for schools and childcare - exploring more.
Want to see it on your photos?
Tell us about your photo-screening situation - we'll be in touch within two business days.