Lynx offers a non‑invasive, AI‑powered platform that lets veterinarians upload photos of canine skin lesions along with health data to receive a rapid diagnostic prediction and confidence score. By automating analysis of biopsies and fine‑needle aspiration alternatives, the service aims to reduce the time, cost, and invasiveness of traditional skin cancer testing for dogs.
Funding
Funding not disclosed
Founders
Product
Problem
Diagnosing canine skin cancer currently relies on biopsies and fine‑needle aspiration (FNA), which are invasive, costly, and require multiple veterinary visits. The delay in obtaining results can postpone treatment decisions and increase stress for both dogs and owners.
Solution
Lynx provides a non‑invasive, AI‑driven platform that enables veterinarians to assess skin lesions from standard photographs combined with patient health data. The system processes the image and clinical information through a trained deep‑learning model and returns a predicted diagnosis with an associated confidence score within minutes. By delivering rapid, remote‑ready insights, Lynx reduces the need for costly biopsy or FNA procedures and accelerates treatment planning. The platform integrates with existing veterinary practice workflows, allowing clinicians to capture lesion images on a smartphone or tablet and receive results directly in their practice management software. This approach improves diagnostic efficiency while maintaining a high standard of care for canine patients.
Target Audience
Primary users are veterinary clinics and animal hospitals that perform skin examinations on dogs and seek faster, less invasive diagnostic tools for skin cancer.
Features
- AI model that analyzes lesion photographs together with health records to generate a diagnosis and confidence metric
- Turnaround time of minutes, enabling same‑visit decision support
- Remote‑ready workflow compatible with standard veterinary imaging devices (smartphone, tablet)
- Secure cloud processing with HIPAA‑compliant data handling for patient privacy
- Integration options for practice management systems via API or web portal
- Continuous model updates based on aggregated anonymized data to improve accuracy over time