Machines that can understand the task before they move.
Xolver helps machines read the work area, understand instructions, and propose useful next steps for review.
Action intelligence is only one part of the system. Proposed behavior still belongs inside a reviewed product workflow.
It adapts when the real world doesn't cooperate.
Most automation breaks when something small changes — a bin moved five centimetres, a part arrived in the wrong orientation, a fixture shifted. The machine stops and waits for a human.
Xolver notices the change and proposes what to do next.
It reads the scene through cameras, understands the task in plain language, and proposes how to proceed — accounting for the physical limits of the machine and the rules you've set.
If it isn't confident, it stops and tells you why — rather than improvising something unsafe.
Sees the scene
Reads the environment through cameras and understands what it needs to do
Adapts in real time
Adjusts the plan as things change — without stopping and waiting
Three things action intelligence changes.
In plain English — what makes it different from traditional industrial automation.
Smooth movements, not jerky commands
Traditional automation gives robots a list of isolated point-to-point commands. Xolver helps propose behavior that can be inspected before the machine acts.
Handles unexpected changes without guessing
Xolver looks ahead by considering likely outcomes before a next step moves forward. If the scene changes, it can re-evaluate rather than blindly continuing.
Works across different robot brands — without reprogramming
Xolver separates task understanding from the specific deployment boundary. Robot fit is reviewed through compatibility and readiness assessment rather than assumed.
Tested in simulation before it touches hardware.
Proposed behavior can be previewed and discussed through application-specific review.
Simulation can generate a reviewable record: what the AI proposed, what changed, and what the team should inspect next.
Public pages describe the review philosophy, not a facility launch claim or operating method.
Motion previews
ReviewableProposed behavior can be discussed before physical work changes.
Operating boundaries
VisibleTeams can see how proposed behavior relates to the limits they care about.
Scene changes
InspectableWhen the environment shifts, the review record makes the change easier to understand.
Audit record
CapturedEach review can preserve what was proposed, what changed, and what needs attention.
Preview before actuation
- Proposed behavior stays visible before physical work changes.
- Unclear situations are brought into review instead of hidden.
- Simulation language is kept high level on public pages.
Smart enough to adapt. Safe enough to trust.
In manufacturing and logistics, a mistake is expensive — in downtime, in damaged parts, in liability. An AI that can improvise isn't just helpful — it's a risk.
Xolver proposes movement. Before any movement reaches the machine, the system checks it against the operating boundary. The AI does not get a shortcut around that review path.
Your rules, enforced automatically
If the AI proposes something that violates your operational rules — like tilting an open container — the system blocks it. Business rules are enforced, not just suggested.
Adjusts for what the machine is carrying
When the payload changes — a heavier part, a different grip — the system adjusts how the robot moves, staying within the safe limits you've defined.
Full audit record, automatically
Every decision, every movement, every safety intervention is recorded. If you ever need to prove what happened — for compliance, insurance, or investigation — the record is already there.
Works with your existing setup.
Xolver is designed to fit alongside existing factory systems where the equipment, task, and deployment boundary make sense.
Works with your existing controllers
Connects to standard industrial control systems — PLCs, ROS2, and similar platforms — so you don't need to rebuild your factory floor to use it.
Runs on-site, not in the cloud
Important behavior runs close to the machine, so reviewed workflows do not depend on a cloud round trip.
Connects to your warehouse and ERP systems
Xolver can use approved task context so the system understands what it is supposed to be doing, not just what it is physically seeing.
Start with a technical assessment.
We'll walk through what Xolver can do in your specific environment — what it handles well, where the edges are, and what a deployment would look like.
FAQ
Can Xolver understand plain-language instructions?
Yes. You describe the task in plain English, and Xolver uses the work-area context to propose a useful next step for review.
Does action intelligence move the robot directly?
No. Xolver separates suggestions from movement. Proposed actions still pass through safety checks, site rules, equipment limits, and operator approval where required.
Can this work with existing robots?
Potentially. Fit depends on the robot, controller, task, site requirements, and deployment boundary. Xolver starts with a compatibility and readiness review.
How should teams think about simulation?
Simulation is a review tool for understanding proposed behavior and discussing next steps. It is not a public promise about facility readiness.
What happens when Xolver is not confident about what to do?
It stops and escalates rather than guessing. An uncertain or unclear situation results in the machine pausing and alerting the operator — with a record of what happened and why.
Does every machine require the same setup?
No. Each engagement depends on the machine, task, operating boundary, site requirements, and review needs.