Advanced Manufacturing
Reduce reprogramming burden for high-mix production.
Industrial robots excel at repetition. But in real-world manufacturing, fixtures move, alignment drifts, and part variants shift daily, making automation brittle.
Task Adaptation via Physical AI.
Industrial robots excel at repetition. But in real-world manufacturing, fixtures move, alignment drifts, and part variants shift daily. Reprogramming for these changes requires weeks of specialized engineering, making automation brittle and expensive.
Zero-Reprogramming Adaptation.
Xolver helps robotic systems evaluate adaptation to variance. Models interpret visual sensory input and propose responses to misalignments, while enforcement and runtime gates decide what can move toward physical behavior.
Technical Precision
- Precise visual guidance for delicate assembly tasks
- Dynamic tolerance handling
Safety Enforcement
- Physics-based safety checks on every proposed motion
- Direct integration with factory control systems
Beyond Computer Vision.
Simply "seeing" the part is not enough. The hard problem is assigning authority over motion. Xolver separates interpretation from execution so model variance can be checked against enforcement gates, runtime contracts, and operator review.
Upgrade your assembly line.
FAQ
Can this help without rewriting the whole automation cell?
That is the goal. Xolver is meant to work with existing plant systems and controllers rather than assuming every surrounding component has to be replaced.
What kinds of production problems benefit most from this approach?
It is most relevant where part variance, alignment drift, fixture movement, or changing visual conditions make hard-coded motion plans expensive to maintain.
What happens when the model is uncertain about a move?
The move should not be treated as automatically valid. Enforcement and runtime behavior are there to reject, hold, or escalate instead of allowing uncertain interpretation to become unsafe motion.