DentalTech · HealthTech Toothly AI
ML diagnostic imaging at scale
At a glance
The brief, up front.
Manual dental X-ray review is slow and inconsistent, across individual practices and multi-site dental service organizations.
The full ML lifecycle, from clinical imaging data and dentist annotation to deployed segmentation and disease-detection models.
The challenge
What stood in the way.
Diagnostic accuracy in dentistry varies widely across providers, and manual X-ray review is time-consuming and subject to human inconsistency. For dental service organizations managing multiple locations, that variability creates clinical and business risk; for individual practices, it limits throughput and patient trust. Toothly AI's vision was to bring the consistency and speed of machine learning to dental diagnostics, as a natural part of the clinical workflow rather than a replacement for clinical judgment.
The system we shipped.
We undertook the complete ML development lifecycle: collecting raw bitewing and X-ray data from clinical partners, building data orchestration pipelines, recruiting dentists as annotators, and using Labelbox to build rigorously labeled training datasets.
From that foundation we built a bespoke model suite performing enamel, pulp, and bone segmentation, tooth classification, and disease detection: cavities, fractures, infections, and bone loss, with production-grade reliability. The platform integrates with existing practice management software and generates structured visual reports that make findings clear to patients, improving case acceptance.
What was delivered
Outcomes you can point to.
- Full ML lifecycle owned end to end: data, annotation, training, deployment
- Enamel, pulp, and bone segmentation, classification, and multi-condition disease detection
- Structured visual diagnostic reports for patient-facing communication
- Integration with existing practice management software, no workflow disruption
- Chewy, a dental AI chatbot aware of clinical regulations, medications, and patient history
Stack
What it runs on.
Your story starts here
Tell us what you're building.
We'll tell you how we'd approach it, and why.