We're Redefining Foot Health with AI

Combining cutting-edge data science with biomechanical expertise to make professional-grade foot analysis accessible to everyone, everywhere.

Our Origin Story

footprint.AI was born from the intersection of two powerful disciplines: data science and biomechanics. Our founders recognized that millions of people suffer from foot-related issues that could be prevented or treated with proper analysis—but access to professional gait labs and podiatrists remains limited.

By leveraging machine learning algorithms trained on extensive biomechanical datasets, we've created a platform that brings lab-grade foot analysis directly to your smartphone. Our AI doesn't replace human expertise—it democratizes access to it.

Every algorithm we develop is validated against clinical standards and refined through collaboration with practicing podiatrists and biomechanics researchers worldwide.

Biomechanics research and data analysis

Built on Scientific Foundation

Our platform is powered by extensive research and validated datasets

100,000+
Gait Datasets

Comprehensive biomechanical data from diverse populations

97.3%
Clinical Accuracy

Validated against gold-standard gait analysis systems

250+
Podiatrist Partners

Collaborative network of foot health professionals

ISO 13485
Certified

Medical device quality management standards

Meet Our Team

A multidisciplinary team of experts united by a passion for improving foot health through technology

Dr. Sarah Chen

Founder & CEO

PhD in Biomechanical Engineering from Stanford. Former researcher at Nike Sport Research Lab with 15+ years in gait analysis and wearable technology.

Dr. Michael Rodriguez

Chief Medical Officer

Board-certified podiatrist with 20+ years of clinical experience. Specializes in sports medicine and biomechanical analysis at leading orthopedic centers.

Alex Kim

Lead AI Engineer

MS Computer Vision from MIT. Former ML engineer at Google Health with expertise in medical imaging and deep learning applications in healthcare.

Scientific research and podiatrist collaboration

Podiatrist-Aligned Design Corrections

Clinical Validation

Every AI recommendation is cross-validated against established podiatric principles and treatment protocols.

Continuous Learning

Our algorithms continuously learn from real-world outcomes and podiatrist feedback to improve accuracy.

Evidence-Based Recommendations

All design corrections are grounded in peer-reviewed biomechanical research and clinical evidence.

Our Mission

To democratize access to professional-grade foot health analysis by combining the precision of clinical biomechanics with the accessibility of smartphone technology, ensuring that everyone can take proactive steps toward better foot health.