Pain assessment in horses still relies largely on in-hand evaluation focused on gait asymmetry in trot, which captures only a limited subset of conditions. Yet, many forms of musculoskeletal or visceral pain primarily emerge under saddle, through behavioural and biomechanical changes that are often interpreted subjectively or attributed to external factors such as training, rider influence or temperament.
This creates a major clinical blind spot, underscoring the need for objective, reproducible tools to assess pain in ridden horses.

The Ridden Horse Pain Ethogram (RHPE), developed by Dr Sue Dyson, is the only scientifically validated method for objectively detecting pain in ridden horses, based on 24 behavioural markers with a proven causal link to pain.
However, its use at scale is limited by the complexity and cognitive load of real-time scoring.
Kairon leverages AI to automate this analysis from simple smartphone videos, enabling fast, objective and scalable pain assessment, with the ambition of becoming the industry's global standard.

1. Proprietary data & technology

• 24 behavioural markers derived from the only scientifically validated ethogram (RHPE)
• ⁠>65 hours of proprietary video data currently under annotation
• ⁠>52,000 annotations already completed, forming a strategic data asset
• ⁠89% accuracy achieved in early training stages on the first marker

2. Scientific validation & field evidence

• 450+ publications and 14,000+ citations from Dr Sue Dyson’s work
• ⁠417 citations specifically related to RHPE research
• ⁠2x higher risk of non-completion in 5* cross-country for horses scoring ≥7 at the warm-up
• ⁠80% of lameness cases linked to compensatory patterns caused by underlying undetected pain (clinical consensus)

3. Market & opportunity

• $300 billion: global equine industry market size
• ⁠#1 cause of economic losses: locomotor pathologies (source: ENVA)
• ⁠Zero: equipment required to use Kairon - only a smartphone is needed