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Towards Healthcare

Veterinary AI Diagnostics Companies, Corporate Growth and Development Strategy

Date : 26 February 2026

Top Vendors in the Veterinary AI Diagnostics Market & Their Offering

Veterinary AI Diagnostics Market Companies are IDEXX Laboratories, Zoetis, SignalPET, Radimal, Vetology

Company Profile

Companies Headquarters Offerings
IDEXX Laboratories Maine, USA Provides advanced diagnostic solutions, including AI-supported imaging, laboratory testing platforms, and cloud-based data management tools to support faster and more reliable veterinary diagnostics.
Zoetis New Jersey, USA Offers AI-enabled diagnostic systems for cytology, hematology, and parasite detection, helping veterinarians improve diagnostic accuracy and streamline in-clinic workflows.
SignalPET Texas, USA Specializes in rapid radiographic interpretation using intelligent software that analyzes X-rays and delivers structured diagnostic insights to support clinical decision-making.
Radimal California, USA Provides cloud-based radiology interpretation services combining automated image analysis with expert review to enhance diagnostic speed and consistency.
Vetology California, USA Focuses on radiology screening and diagnostic support solutions that assist veterinarians in identifying abnormalities early through intelligent image evaluation.
Aiforia Helsinki, Finland Develops deep-learning image analysis platforms for digital pathology, supporting faster and standardized evaluation of tissue and cytology samples in veterinary laboratories.
Moichor California, USA Delivers in-clinic diagnostic tools for blood and cell analysis, enabling rapid preliminary results and supporting early disease detection.
Scopio Labs Tel Aviv, Israel Offers high-resolution digital microscopy and analysis platforms that support remote review and enhanced interpretation of blood and pathology samples.

Value Chain Analysis

R&D

  • Research and development in veterinary diagnostics is progressing rapidly, with emphasis on advanced imaging, pathology systems, and wearable monitoring tools to improve diagnostic accuracy, reduce clinician workload, and support early disease detection.
  • Key industry: Zoetis, Heska, IDEXX Laboratories, Mars Petcare, and Antech Diagnostics.

Clinical Trials

  • Clinical trials in veterinary diagnostics are progressing quickly, with efforts centered on improving diagnostic precision and workflow efficiency across imaging, pathology, and disease monitoring applications. These studies aim to validate performance in real clinical settings and support earlier, more reliable detection.
  • Key players: GE HealthCare, FUJIFILM Healthcare, Agfa HealthCare, SignalPET, and Mindray.

Patient Support and Services

  • Veterinary diagnostic support solutions deliver fast, real-time insights across imaging, pathology, and clinical data, helping clinicians detect conditions earlier and plan treatments more effectively. Acting as decision-support systems, they simplify workflows and improve collaboration among care teams.
  •  Key players: Covetrus, VCA Animal Hospitals, Sound Diagnostics, Vetspire, and PetsApp.

Market Growth

The global veterinary AI diagnostics market size was estimated at USD 798.42 million in 2025 and is predicted to increase from USD 936.06 million in 2026 to approximately USD 3917.31 million by 2035, expanding at a CAGR of 17.25% from 2026 to 2035.

Veterinary AI Diagnostics Market, Size is USD 936.06 Million in 2026.

What are the Recent Developments in the Veterinary AI Diagnostics Market?

  • In November 2025, Vetology partnered with dvmGRO to bring intelligent radiology reporting and teleradiology services to dvmGRO’s independent clinic network. The partnership enables easier access to advanced diagnostic capabilities, improving diagnostic accuracy and workflow efficiency through scalable support and customized onboarding for member practices.
  • In October 2025, MI: RNA received funding to advance a blood-based diagnostic tool that uses microRNA biomarkers for earlier, non-invasive identification of osteoarthritis in dogs. The project combines biomarker analysis with advanced modeling to improve disease detection and staging, reducing dependence on traditional imaging and subjective evaluations.

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