VideaHealth provides an AI‑driven platform that automatically analyzes 3D intraoral scans and 2D dental radiographs to detect caries, bone loss, and other pathologies, delivering pixel‑level segmentation maps and confidence scores. The results are delivered via a secure web dashboard and can be exported through DICOM‑RT and HL7 FHIR APIs for seamless integration with practice management and EHR systems. Cloud‑native inference runs in under five seconds per image and includes audit logging for regulatory compliance.
Funding
$40M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Dental clinicians must manually interpret intraoral scans and radiographic images, a process that is time‑consuming, prone to inter‑operator variability, and can miss early-stage caries or subtle periodontal bone loss.
Solution
VideaHealth delivers an AI‑enabled diagnostic platform that automatically analyzes 3D intraoral scans and 2D dental radiographs to flag carious lesions, alveolar bone defects, and other common pathologies. The service leverages deep convolutional neural networks trained on a curated, HIPAA‑compliant dataset, producing pixel‑level segmentation maps and calibrated confidence scores for each finding. Results are streamed to a secure web dashboard where clinicians can review annotated images, export structured reports, and receive triage recommendations. The platform integrates with practice management and imaging systems via DICOM‑RT and HL7 FHIR APIs, enabling seamless workflow incorporation without additional hardware. Cloud‑hosted inference ensures rapid turnaround (typically under 5 seconds per image) and supports continuous model refinement aligned with emerging clinical guidelines. An audit‑log module records all AI‑generated outputs for regulatory compliance and quality‑control purposes.
Target Audience
The primary customers are general dental practices, orthodontic and periodontic clinics, and dental imaging laboratories that require fast, reproducible interpretation of intraoral scans and radiographs.
Features
- Deep‑learning engine (ResNet‑based CNN) optimized for dental radiography and intraoral optical tomography
- Automated lesion segmentation with per‑pixel confidence metrics and false‑positive suppression
- DICOM‑compatible upload pipeline and HL7 FHIR‑based result export for EHR/PM integration
- Real‑time web dashboard offering annotated image overlays, downloadable PDF reports, and treatment‑priority flags
- Cloud‑native inference service with auto‑scaling GPU instances delivering sub‑5‑second analysis latency
- End‑to‑end encryption (TLS 1.3) and role‑based access control meeting HIPAA and GDPR requirements
- Continuous model update cycle via federated learning on anonymized practice data
- Built‑in audit trail capturing timestamped AI decisions for compliance reporting