ABOUT VERMILION
Industrial reasoning, grounded in physics.
We're building physics-informed reasoning for industrial reliability: predictions that respect conservation laws and explain themselves in your team's language.
ψ(q, p) · STABLE3 : 2
PHASE SPACE · CLOSED
PHYSICS-FIRST · GROUNDED∮ ENERGY · CONSERVED
PRINCIPLESHow we build,
How we build,
and what we won't ship.
Three commitments that shape every model we deploy.
01
A prediction is a chain of physical inferences. Not a black-box score.
02
Confidence is a probability, not a vibe. Calibrated, published, audited every quarter.
03
A model that can't be explained step-by-step doesn't ship to a reliability team.
OUR JOURNEY
From concept to commercialization.
A short timeline of how Vermilion got here, and where we're headed.
2022
The Founding
Vermilion was founded by Sean Smith, Eng. after identifying a gap in market for predictive health and usage-monitoring systems.
2023
Research
First Physics-Informed Neural Network architecture trained on bearing-dynamics data, with an initial focus on aerospace assets.
2024
LRM v1
Reasoning core released into production.
2025
LRM v2
Cross-fleet learning enabled (opt-in).
2026
Commercialization
Production-ready and available for worldwide deployment, with targeted solutions for every major industrial sector.
READY WHEN YOU ARERun your operation smoothly,
Run your operation smoothly,
predictably, indefinitely.
See Vermilion reason about a real failure mode in your environment. Thirty minutes, with one of our reliability engineers.