Research & Accuracy

Scientific honesty and credibility. We publish our methodology, accuracy targets, and known limitations.

Current Accuracy Targets

~75%
MVP Overall Accuracy

This represents our current target for the minimum viable product. Accuracy varies by condition and element type.

High-confidence indicators80-85%
Medium-confidence indicators70-75%
Low-confidence indicators60-70%

Methodology

Element Definitions

Each facial element is defined with clear boundaries, measurement criteria, and sub-classifications. Definitions are based on established facial analysis literature.

Weighting Logic

Condition correlations use weighted matrices where element contributions are determined by clinical literature and validation studies.

Confidence Scoring

Confidence tiers are calculated based on element correlation strength, image quality factors, and historical validation data.

Validation Process

Results are validated against clinical outcomes through ongoing research partnerships and anonymized outcome tracking.

Known Limitations

We believe in transparent communication about what our system can and cannot do. These limitations are actively being addressed in our research roadmap.

Lighting Conditions

Extreme lighting (too bright/dark) can affect element detection accuracy.

Skin Tone Variations

We're actively working on improving accuracy across all skin tones through diverse training data.

Camera Quality

Low-resolution cameras may reduce element detection precision.

Facial Obstructions

Glasses, makeup, or facial hair may affect certain element measurements.

Bias Mitigation Roadmap

Phase 1 - Current

Diverse Training Data

Expanding training datasets to include diverse demographics, skin tones, and age groups.

Phase 2 - Q2 2026

Fairness Audits

Regular third-party audits to identify and address accuracy disparities across groups.

Phase 3 - Q4 2026

Adaptive Models

Implementing adaptive calibration based on user demographics for improved accuracy.