Most AI verification focuses on the “brain,” but the real challenge is how that brain talks to analog sensors. Our approach uses RNM modeling to translate complex analog signals into a language the digital DMS environment can understand. By syncing these “senses” with the digital logic, we create a unified simulation that behaves like real hardware. This allows us to identify timing and signal mismatches between the AI core and its analog inputs months before silicon, dramatically reducing post-silicon risk and ensuring our partners a system stability.
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