Design Automation Across Advanced Process Nodes

Semiconductor design at advanced process nodes is becoming exponentially more complex. AI-driven design automation reduces the iteration burden on engineering teams and compresses tape-out timelines without sacrificing design quality or manufacturability.

The Challenge

As chip complexity scales with Moore's Law, EDA tools alone cannot keep pace with the combinatorial explosion of design decisions at advanced nodes. Design teams spend significant time on manual optimisation passes that could be automated, delaying time-to-silicon on critical product programmes.

Our Approach

• AI-assisted place-and-route — Reinforcement learning models that explore layout configurations and identify high-quality solutions faster than conventional EDA optimisation.
• Design-for-manufacturability automation — AI analysis of layout patterns against process design rules, flagging DFM violations and suggesting alternatives before tape-out.
• Automated design verification — ML models that predict simulation outcomes and focus verification resources on high-risk design areas, reducing full simulation runtime.

The Outcome

Design teams that integrate AI automation into their EDA workflows compress product cycles and reduce costly respins — competitive advantages measured in months rather than percentage points.