Leveraging AI-Assisted Tools for End-to-End Productivity: Synopsys.ai Copilot Program

Featured Speakers:

• Frank Lavagni, GPU RLS-TFM lead, Intel 

The Synopsys.ai Copilot program addresses the complexity of physical design and signoff by using AI assistants to improve productivity and reduce design cycles. Pilot results show the Knowledge Assistant (KA) delivers fast, accurate answers, simplifies tool and VLSI understanding, enhances knowledge sharing, and cuts troubleshooting time from hours to minutes through clear root cause insights and fixes. Looking ahead, KA and the upcoming Workflow Assistant (WA) are expected to further accelerate workflows with intelligent recommendations, code generation, and automation—helping speed timing convergence, reduce ramp-up time for engineers, and enable more efficient end-to-end design optimization.

Highlights

• Fast, accurate AI assistance that reduces documentation and troubleshooting time from hours to minutes
• Improved knowledge sharing via BKM distribution plus error/warning severity and resolution guidance
• Expected productivity uplift from automated scripting, optimization, and faster engineer ramp-up through WA/KA integration