Biologically plausible mechanism like homeostasis compliments Hebbian learning to allow unsupervised learning in spiking neural networks . In this work, we propose a novel ferroelectric-based quasi-LIF neuron that induces intrinsic homeostasis. We experimentally characterize and perform phase-field simulations to delineate the non-trivial transient polarization relaxation mechanism associated with multi-domain interaction in poly-crystalline ferroelectric, such as Zr doped HfO2, that underlines the Q-LIF behavior. Network level simulations with the Q-LIF neuron model exhibits a 2.3x reduction in firing rate compared to traditional LIF neuron while maintaining iso-accuracy of 84-85% across varying network sizes. Such an energy-efficient hardware for spiking neuron can enable ultra-low power data processing in energy constrained environments suitable for edge-intelligence.