A photo improvement hub grounded in 160 years of facial psychology research.
Most people know their photos aren't great but don't know why. They can't get honest feedback from friends, professional photographers are expensive, and generic "smile more" advice doesn't help.
RealSmile was built to solve this. We combined decades of facial psychology research with modern AI to give anyone instant, honest, science-backed feedback on their photos — for free.
The result is a photo improvement hub used by people on Tinder, Hinge, Bumble, and LinkedIn who want to make better first impressions without guesswork.
French neurologist Guillaume-Benjamin-Amand Duchenne de Boulogne identified that genuine smiles involuntarily activate two facial muscles simultaneously: the zygomaticus major (mouth corners) and the orbicularis oculi (eyes). Fake smiles only use the mouth. This discovery became the foundation of modern facial expression research.
Paul Ekman and Wallace Friesen created FACS, a comprehensive system for categorizing human facial movements. Their research confirmed Duchenne's findings and showed that humans can detect fake smiles in as little as 33 milliseconds — faster than conscious thought.
Researchers at UC Berkeley analyzed yearbook photos of 141 women and found that those with genuine Duchenne smiles had better life outcomes 30 years later — better marriages, higher wellbeing scores, and greater personal satisfaction. The smile in a photo predicts real-world success.
Modern facial landmark detection AI can now analyze the 68 key points of a human face in milliseconds, identifying whether a smile engages the eye muscles (genuine) or only the mouth (forced). RealSmile uses this technology to give instant feedback anyone can act on.
The AI identifies 68 key points on the face including eyes, eyebrows, nose, and mouth corners.
It measures whether the orbicularis oculi (eye muscles) are engaged alongside the mouth — the signature of a Duchenne smile.
A score from 0-100 reflects how genuine the smile appears based on the ratio of eye to mouth muscle engagement.
The AI uses @vladmandic/face-api, a state-of-the-art facial analysis library built on TensorFlow.js. On desktop browsers, analysis runs entirely client-side — your photo never leaves your device. On mobile, photos are processed via a secure server and immediately discarded. No photos are ever stored or used for training.
Desktop analysis runs entirely in your browser. Mobile photos are processed on our secure server and immediately discarded after analysis.
We do not build profiles, store biometric data, or use your photos for AI training. Analysis is one-time and ephemeral.
You can use the analyzer completely anonymously. We do not require email, login, or any personal information.
We use Google Analytics to understand which guides are helpful. No personal data is collected or shared.
Upload a photo and get your smile authenticity score in seconds.
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