NoveetyAI was founded to turn three decades of published VLSI reliability, thermal and computation research into production chiplet design software — independently implemented, engineered for speed, and callable by an autonomous agent.
Advanced packaging changed the shape of the problem. In a 2.5D or 3D chiplet system-on-package, electrical, thermal, reliability and mechanical physics are coupled — IR-drop drives Joule heating, heat drives electromigration and thermomigration, thermal mismatch drives warpage. Analyzed separately and checked last, each answer is misleading.
We build the simulation engines that are accurate enough to sign off on and fast enough to sit inside an optimization loop — then we make them callable, so an autonomous design agent can evaluate thousands of candidates against real physics rather than a surrogate.
Every engine ships with a ground-truth reference solver, and every result is validated against it.
Order-of-magnitude acceleration is what makes closed-loop optimization possible at all.
CLI-first, structured I/O, headless by default. No GUI in the loop.
Support for OpenROAD alongside commercial flows keeps the door open for research and small teams.
Prof. Tan directs the VLSI System and Computation Lab (VSCLAB) at UC Riverside, where the NoveetyAI engines originated. His research spans VLSI reliability modeling, thermal analysis and management, hardware acceleration, and AI/LLM-driven approaches to electronic design automation.
The algorithm behind each NoveetyAI engine was first published as peer-reviewed research from VSCLAB — open literature, available to anyone — and validated against a reference solver on industrial-scale benchmarks: IBM power-grid circuits, SAED32 place-and-routed designs, and real measured power maps from Snapdragon, Coral Edge-TPU, and Intel Core processors. We then built our own production implementation of each method: engineered for loop speed, CLI-first, structured I/O, and supported as a commercial product.
Spectral thermal solver for 2.5D/3D stacks. 30 cases benchmarked against 3D FEM.
2D laminate + 3D layer-wise FEM warpage. Nine benchmark packages, 3–11 layers.
Advanced Krylov subspace reduction for transient power-grid analysis. Validated to 1.04M nodes.
The methods behind these engines were developed in academic research at the University of California, Riverside and published in the peer-reviewed literature, where they are available to the public. NoveetyAI's software is an independent implementation of those published methods — it is not licensed from, distributed by, or derived from software belonging to UCR. NoveetyAI, Inc. is an independent company; UCR does not endorse its products or services.
Tool access, an evaluation on your own designs, or a design-services engagement — start here.