Why it matters
Without AI, misreads of hoof angles, incorrect shoeing intervals, and inconsistent farrier notes risk welfare decline, performance gaps, and regulatory non-compliance across entries, inspections, and withdrawal timelines.
From design to safety
Design
AI supports design and selection
The system aggregates hoof health indicators, plate type options, shoe materials, baseline sensor readings, and gait profiles to propose an initial shoeing strategy and selection criteria.
- racing plates
- aluminium shoes
- hoof angle gauge
Build
AI guides build integration
During installation, it records baseline hoof measurements, plate alignment, fastener torque, bedding compatibility, and tool calibration to ensure proper fit, traceability, and calibration consistency.
- hoof angle gauge
- racing plates
- hoof rasp
Operation
AI monitors daily shoeing status
Continuous reads from hoof angle data, shoeing intervals, and farrier notes feed real-time checks for consistency, gait stability, and early anomaly detection linked to race entries and workload.
- aluminium shoes
- shoeing intervals record
- farrier notes log
Maintenance
AI supports maintenance workflows
Periodically rechecks hoof health metrics, plate fit, edge wear, stud hole integrity, and rasp wear; it flags deviations, schedules adjustments, and logs communication trails with the farrier team.
- hoof angle gauge
- racing plates
- hoof rasp
Safety
AI enforces safety and compliance
Records are audited against medication controls, passport details, stable inspections, and rider safety protocols; alerts trigger corrective actions to maintain humane care and regulator alignment.
- farrier notes log
- shoeing intervals record
- racing plates
Part by part
- 1
racing plates
- Watch for
- wear mismatch at plate edges or loosened fittings that alter gait and can cause subtle asymmetry under sprint work
- AI action
- read plate alignment data; trigger maintenance alert to senior farrier and schedule immediate re-fit
- 2
aluminium shoes
- Watch for
- poor edge wear, delamination risk, or loose fastenings compromising traction during fast gallops
- AI action
- monitor shoe integrity; flag replacement need and schedule fitting; log action to shoeing ledger
- 3
hoof angle gauge
- Watch for
- drift in hoof angle beyond safe thresholds, including during load tests
- AI action
- compare current vs baseline angles; prompt corrective shoeing plan and document deviation
- 4
shoeing intervals record
- Watch for
- inconsistent intervals across horses or missed deliveries including last-minute raceday changes
- AI action
- calculate optimal interval; generate schedule and rider notifications; export to passport system
- 5
farrier notes log
- Watch for
- missing or inconsistent entries across horses or conflicts with owner notes
- AI action
- verify entries against care plan; escalate gaps to yard manager for sign-off
- 6
hoof rasp
- Watch for
- tool wear or improper use flagged by sensor, including dull blades or improper seating
- AI action
- audit tool condition; trigger maintenance check for equipment sanitation and replacement
Worked example
Catching a hoof angle drift before a plate change
Illustrative scenario with sample data.
A jockey reports a horse showing subtle gait stiffness after a training session, prompting a proactive plate evaluation ahead of a sprint handicap.
Signal in
hoofAngleBaseline=14.2; currentAngle=15.6; plateFit=good; shoeingInterval=28 days; farrierNotes=recent shoeing; horseID=H-402; trainerNote=priority: medium; gaitScore=6.1; travelLog=week-2; maxDailyLoad=7
System out
alert: hoof angle drift detected; recommend re-check and possible re-shoeing; maintenance task ID M-742; schedule with Farrier J; update race entry risk to medium; risk category: gait asymmetry; re-measure in 7 days; add record to passport
Human sign-off: Yard manager reviews AI alert and approves a re-shoeing with the lead farrier after confirming workload and upcoming race; sign-off completed in the care plan.
How to roll it out
Phase 1
Weeks 1 to 4
Baseline data collection, establish acceptable ranges, calibrate sensors, train staff to interpret alerts, and link to stable inspection protocols.
Phase 2
Weeks 5 to 8
Run full integration with live horses, refine thresholds, implement alert routing to farrier notes, and test cross-checks with passport and vaccination records.
Phase 3
Weeks 9 to 12
Stabilize workflow, tie into medication control, withdrawal times, and regulator checks while maintaining auditability across all records.
Where people stay in charge
- All decisions affecting shoeing must be signed off by the licensed trainer or yard veterinary surgeon.
- AI actions involving medication or withdrawal implications must be reviewed by the racing regulator or designated authority.
- AI outputs must be auditable with time-stamped edits and human overrides available.
Questions owners and crews ask
What data do I need to start AI farrier analysis for my yard?
Begin with baseline hoof angles, plate types, shoeing intervals, and a stable notes log; ensure all horses have up-to-date passport, vaccination records, and a clean medication history.
How does AI suggest shoeing intervals without overloading horses?
AI analyzes historical interval data, hoof health trends, workload, and race commitments to propose individualized, compliant scheduling that preserves gait integrity and soundness.
Who approves changing a horse’s shoeing plan based on AI findings?
The licensed trainer, yard veterinary surgeon, and head lad review AI recommendations and authorize the shoing plan change after field verification.
What regulatory considerations does the system address?
It aligns with stable inspections, medication control, withdrawal times, and regulator checks by flagging any non-conforming hoofcare actions and maintaining traceable records.