Ferroelectric device has been widely investigated as a candidate to replace the charge trap device in NAND flash owing to its low operating voltage, high speed, and structural similarity to conventional cell. Moreover, it has potential to be utilized for the compute-in-memory applications targeting energy-efficient processing of ultra-large AI models. In this talk, the current device-level research progresses on ferroelectric NAND (FeNAND) will be presented briefly, then the array-level NAND cell simulator designed to assess the feasibility of ferroelectric cell will be introduced. Following this, its potential and applicability to compute-in-memory architectures will be discussed.