Reliable industrial labor for the high-variance work traditional automation can't handle.
Industrial cells are built for repeatability, but real production environments are full of variation: failed picks, skewed items, bad scans, packaging variance, ambiguous inspection. The hard part isn't running the happy path once. It's keeping a cell running when reality drifts. Today, humans still supervise and recover, which is why most high-mix work never reaches an automation ROI worth pursuing.
Mithril turns physical AI into deployable robot labor. We combine modern robotics models with the full deployment stack: multi-camera perception, task execution, recovery behaviors, and workflow-specific context, all inside a single system that runs on top of the cobots and infrastructure customers already own. When the environment deviates, the cell adapts, retries, recovers, and routes exceptions instead of stopping the line.
Foundation models, vision, and edge compute have crossed the threshold where robots can reason through ambiguity that used to break scripted automation. The bottleneck has moved from capability to reliability. That's where the value sits, and that's where we build.
We start in reverse logistics, packaging, kitting, inspection, and machine tending: high-mix work that today depends on human supervision to stay running. Every deployment makes the next one smarter.