Compute-in-Memory (CIM) is a promising non-von Neumann computing paradigm that promises unprecedented improvements in performance and energy efficiency. Moving past manual designs, automation will be key to unleash the potential of CIM for multiple application domains and to accelerate cross-layer design cycles. This talks reports on an ongoing effort to build a high-level compiler infrastructure for different CIM approaches, built with MLIR to abstract from individual technologies to foster re-use. This includes abstractions and optimizations flows for logic-in memory, content-addressable memories, arithmetic operations in crossbars, and near-memory architectures. We also report on recent results retargeting the compiler for novel ferroelectric cells, exploring different memory modalities.