Enforcement Layer
The deterministic gatekeeper for physical AI.
Even the most advanced robotics foundation models produce probabilistic intent. Physical systems, however, are strictly deterministic. A dropped part, a moving obstacle, or an ambiguous prediction can result in catastrophic failure if not bounded by physics.
A Physics Compiler for AI.
The Xolver Enforcement Layer solves the variance problem by acting as a "Physics Compiler." It intercepts high-level AI intent and translates it into mathematically proven, collision-free, and safe execution trajectories in real-time.
Deterministic Mathematics
Our JAX-native Kinematics Engine ensures that 100% of proposed trajectories are physically valid before any hardware moves.
Zero-Tolerance Collision
Advanced Cartesian Barrier Projections actively regulate velocity to guarantee that the system never collides with its environment (e.g., floors, tables, or safety cages).
Intelligence, bounded by reality.
We believe that physical intelligence without hard boundaries is a liability. Model outputs must be constrained by the laws of physics and operational safety policies. Xolver's Layer 2 uses formal methods—specifically Operational Space Control Barrier Functions (OSCBF)—to mathematically guarantee the safety of every single move.
Kinematic Feasibility
Real-time forward and inverse kinematics validate complex 7-DOF configurations instantly, ensuring singularity-free motion.
Action Space Normalization
The Enforcement Layer bridges the gap between deep learning and electrical engineering, seamlessly converting VLA (Vision-Language-Action) logits into rigid, safe physical units like m/s and rad/s.
Explicit Failure Behavior
Halt. Log. Escalate.When a foundation model proposes an action that violates collision boundaries or joint limits, the Enforcement Layer doesn't improvise. It gracefully halts motion, logs the deviation for reflective adaptation, and safely escalates.
Engineered for trust in production.
Because the physical world does not wait for a cloud API response, the Enforcement Layer is designed to operate seamlessly at the edge, acting as an uncompromisable shield.
High-Performance JAX-Native Solver
Calculates real-time safety manifolds and intervention boundaries in less than 5ms, operating well within strict industrial latency budgets.
Unified Action Intent
Dynamically supports both single-step action tokens and complex, multi-step trajectory chunks, allowing maximum flexibility for the foundation models above it.
Backbone-Independent Safety
Whether you're running our Autoregressive (X1) or Diffusion (X1-D) models—or even testing bleeding-edge experimental models—the Enforcement Layer guarantees absolute physical baseline safety regardless of the generative process.
Ready to deploy safety-first autonomy?
Stop compromising between intelligent adaptability and deterministic safety. Deploy AI that respects reality.