Clinical Validation // ROADMAP_V2.5

Clinical Roadmap

AIVET is not a static product; it is a rigorous clinical validation pathway. We are instrumenting, quantifying, and validating the signals that bridge the cross-species gap.

Launch Grimace Hub View Protocols

Neural Training Methodology

Our neural models are trained using Expert Consensus Mapping. We collect high-resolution clinical data and have it manually annotated by board-certified DVMs and behavioral specialists.

Neural Training Matrix
Figure 1.2
Consensus Matrix Visualization
Dataset Diversity150,000+ clinical frames across 42 breeds, diverse lightings, and clinical environments.
Validation LoopsEvery inference model is cross-validated against the Glasgow Composite Measure Pain Scale (CMPS).

Release Timeline

LIVE PROTOCOL
Q1 2026VERIFIED (κ>0.82)

Calibration

Baseline calibration of the 48-node facial landmark engine against the Feline Grimace Scale (FGS).

Q2 2026IN SITU TESTING

Acoustic Flux

Spectral centroid decomposition for automated nociceptive distress detection in canine vocalizations.

Q3 2026STAGING

Bayesian Fusion

Multi-modal consensus (Visual + Audio + Vitals) for high-confidence diagnostic support.

Q4 2026PLANNED

Scale Expansion

Heterogeneous dataset expansion to 500k+ validated frames across 12 diverse species.

Active Consensus

Total Votes14,203
Active Agents24
Join Validation Network

Human Application

While developed specifically for veterinary use, the underlying AIVET Signal Protocol is mathematically suitable for human clinical application—including non-verbal pediatric monitoring and geriatric comfort assessment.

*Human application requires site-specific legal and clinical authorization in your local jurisdiction.

Human Application Mesh