Education
Master of Data Science, UWA. Bachelor of Commerce, Finance, Curtin.
Matthew Haskins · Perth, Western Australia
Matthew Haskins
Hi - I built FaceGate.
I’m a data scientist and AI engineer based in Perth. I work on applied machine-learning systems - particularly the kind that have to be reliable, explainable, and easy for non-technical people to use.
I built FaceGate because the same problem kept coming up in conversations with friends who work in the childcare industry - the trickiness of publishing children’s photos responsibly.
Find me
Credentials
The shape of the work I do.
Professional
AI Engineer at EY - digital-asset assurance, blockchain analytics. Prior finance and tax roles.
Research
Master's thesis on temporal Graph Neural Networks for rumour detection.
Practice
Builds full-stack tools across AI, data visualisation, and developer tooling. Cares about design, clarity, and things that work.
The story
Why I built this.
The conversation that kept coming up in 2024 was the same one. Schools and childcare centres take a lot of photos. Some of those photos contain children whose families have asked for them not to appear in newsletters, on social, or in the yearbook. The systems for tracking who’s consented to what are usually spreadsheets and inboxes. The system for actually checking before a photo goes out is usually a person, eyeballing a hundred photos at the end of a long day.
Off-the-shelf face recognition exists, but the answer it gives a school is the wrong shape: send photos of children to a vendor’s servers, and trust that vendor with biometric data. Solving a privacy problem by creating a new one.
The brand promise is the architecture. The phone is the only computer involved.
FaceGate is the version that doesn’t do that. The phone is the only computer involved. The consent list lives on the device, the matching runs on the device, the audit log stays on the device. There is no FaceGate server because there is no FaceGate server to build.
What I deliberately didn’t build is just as important: no cloud upload, no user login, no telemetry beyond the standard app-store metrics, no “social features”, no live chat support widget that watches every page.
The interesting work was making this useful for people who don’t care about the architecture. A Marketing Coordinator at a primary school shouldn’t need to think about cosine similarity. The app gives them a verdict per photo, the option to override it, and an audit trail. That’s the whole product.
How we work
What working with FaceGate looks like.
Deployment
Comes ready on a pre-configured device
FaceGate ships on a recommended Android device, set up and included with your licence - known-good hardware, no admin panel to roll out, no IT integration to schedule.
Operator-owned
Your data stays your data
Consent list, audit log, photos - everything lives on the device. No vendor copy, no central store, no third-party share.
Engagement
Direct line, not a queue
Onboarding is a single call. Ongoing support reaches the team building the app directly - no tier-1 queue, no ticket back-and-forth.
If you’re thinking about FaceGate for your organisation, I’d rather hear about your workflow before pitching mine. Get in touch.