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 teams review how robotic systems respond to variance. Models can interpret changing context and propose responses, while the product keeps review and operating boundaries visible.
Sentinel keeps production exceptions, machine health, interventions, and readiness records visible so teams can understand what changed and decide what should happen next.
Precision Work
- Precise visual guidance for delicate assembly tasks
- Dynamic tolerance handling
Reviewable Operation
- Clear review before physical work changes
- Operating records teams can understand later
Beyond Computer Vision.
Simply "seeing" the part is not enough. The hard problem is making changing work understandable to the people responsible for it. Xolver separates interpretation from review so teams can inspect what changed and why.
Tactile state becomes operating context.
Some factory tasks cannot be solved by vision alone. Assembly, sorting, insertion, packaging, and delicate part handling often depend on what happens at the point of contact. Xolver now supports tactile and dexterous manipulation workflows, helping robots monitor grip, contact, and safety state while operating inside approved limits.
Example
“Pick the component gently, confirm stable contact, and stop if the grip becomes unsafe.”
Outcome
The robot can use tactile state as part of its operating context, helping reduce dropped parts, forced insertions, unsafe handling, and unexplained failures.
Best-Fit Workflows
- Delicate part handling
- Grip-aware pick and place
- Assembly and insertion tasks
- Sorting parts with variable geometry
- Packaging workflows where pressure and placement matter
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.