Should You Build Your Own AI-Assisted Silicon IP and EDA Tools? A Brutally Honest Analysis

The question lands on the desk of every engineering VP at a growing fabless firm, usually after a painful licensing renewal: Do we keep paying ARM and Synopsys indefinitely, or do we build our own stack?

It is not a hypothetical anymore. India's Saankhya Labs built proprietary baseband IP rather than licensing a standard modem core and won a contract for the Indian Railways broadband network on the back of it. Chennai-based InCore Semiconductors shipped a RISC-V application processor core by betting entirely on open ISA and in-house verification flows. Meanwhile, at the hyperscaler end, Google's TPU program and Amazon's Graviton are the canonical proof that in-house silicon IP, built with proprietary EDA customizations, is viable at scale and strategically irreversible once done.

But for every success, there are quieter failures: startups that spent two years building custom place-and-route scripts only to discover that TSMC's sign-off requirements demanded a Cadence Innovus run anyway. The decision is high-stakes and deeply context-dependent. This article gives you the framework to make it correctly for your organisation.

 The Landscape in 2026
The globa...