Intellectual Property & Innovation
Protecting the future of bounded physical AI.
At Xolver, we believe the transition from "software AI" to "physical AI" requires fundamental breakthroughs in how machines understand their own limitations. Standard AI models are built to predict. Xolver is built to evaluate physical intent with explicit safety rules, deployment evidence, and boundaries defined before any machine moves.
Our growing patent portfolio protects the core systems that make robotic behavior more inspectable, auditable, and capable of bounded autonomy in unpredictable real-world environments.
Status: Patent Grant Pending
The Challenge
Generative AI models can sometimes "hallucinate" impossible physical moves—like planning a trajectory that requires a robotic arm to bend backward or pass through its own body. Standard systems only figure this out when the robot physically crashes.
The Xolver Innovation
We invented an active "imagination filter." During the moment the AI is deciding what to do, our framework projects the proposed move through strict physical checks. If the move violates a declared mechanical limit, the proposal can be redirected, blocked, or escalated before a motor command is allowed.
Status: Patent Grant Pending
The Challenge
Most AI robots rely almost entirely on vision (cameras). But in industrial settings, if a gear slips, a motor grinds, or a fragile object starts to crack, a camera often won't register the failure until the damage is already done.
The Xolver Innovation
We endowed our systems with an independent edge "nervous system" that listens to high-frequency audio and monitors electrical currents in the robotic joints thousands of times a second. If the system "hears" or "feels" an anomaly, it completely bypasses the slower visual AI brain and triggers an instant, compliant physical yield.
Status: Patent Grant Pending
The Challenge
Tell a standard robot to "wipe the table," and it only calculates coordinates (where to move). It doesn't natively grasp how much force it should apply, treating "wipe the table gently" and "wipe the table firmly" as the exact same physical command.
The Xolver Innovation
We developed an architecture that allows the robot's AI to translate simple descriptive adjectives (like "gently", "firmly", "loosely") directly into physical tension. Our system intuitively adjusts the stiffness and damping of the robotic joints on the fly, allowing the robot to change how hard it pushes based entirely on the natural language you use.
FAQ
What does Xolver's patent portfolio cover?
The portfolio covers core innovations in bounded physical AI: real-time physics constraint enforcement, cryptographic evidence records for machine actions, natural language to physical tension translation, and the architecture that separates model reasoning from deterministic actuation.
What is the Physics Compiler and why is it patented?
The Physics Compiler is a deterministic enforcement layer that validates every planned motion against mathematical constraints — joint limits, force envelopes, collision zones — before any command reaches hardware. The patent protects the architecture that makes unsafe motion impossible rather than just unlikely.
What is the Evidence Record patent about?
The Evidence Record system cryptographically seals every machine decision, permitted action, refusal, and near-miss event at the time it occurs. The patent protects the method of generating tamper-proof audit trails that can be used for regulatory review, insurance, and operational accountability.
Are Xolver's patents available for licensing?
OEMs, system integrators, and enterprise operators interested in licensing discussions can reach the commercial team via the contact page. Each engagement starts with a technical assessment.
Building the standard for auditable robotics.
Are you an OEM, system integrator, or enterprise looking to leverage auditable, predictable physical AI?