PCBs that work. / First iteration.
Reinforcement learning generates multiple PCB layout candidates with physics-validated traces — in hours instead of weeks.
Set it once. Applied everywhere.
GerberGPT manages every project setting — board dimensions, layer stackup, design rules, and constraints. Configure once, and the AI applies them consistently across every generated iteration.
Every trace, checked before you see it.
Each trace is validated against electromagnetic constraints, thermal limits, and signal-integrity requirements during generation — not after.
The reinforcement-learning model understands the physics of electronics design, so layouts meet real-world performance requirements from the first candidate.
Built on reinforcement learning.
Deep Learning Models
Trained on vast datasets of successful layouts, the models understand the relationships between component placement, routing, and performance.
Physics Simulation
Real-time electromagnetic and thermal simulation ensures every design meets performance requirements before manufacturing.