Rethinking RTL flows with AI-driven hybrid formal verification

By Praveen Kumar Vagala

September 29, 2026

Modern RTL verification flows generate more evidence than engineers can always review with equal priority. Simulation, assertions, coverage, and formal analysis each expose different classes of behavior, but a large design can produce hundreds or thousands of properties.

This article describes an AI-assisted workflow that uses machine learning to prioritize those properties while leaving proof and counterexample generation to the formal engine. The approach is intended to complement, not replace, established SystemVerilog, Universal Verification Methodology (UVM), simulation, and formal verification practices.

The problem: too many properties, too little verification time

Verification teams face a practical allocation problem. A complex subsystem may include control-state logic, FIFO interfaces, arbitration, multiple clock domains, configuration registers, error handling, and protocol checks. Each area can generate assertions, and each assertion can have a different verification cost and value. Some properties prove quickly. Others expose difficult corner cases or consume substantial solver resources.

To read the full article, click here