An innovative approach merging coordinate-based learning with seismic modeling to efficiently invert post-stack seismic data. Through practical applications on both synthetic and field datasets, IntraSeismic has proven to surpass traditional variational and deep-learning-assisted methods in delivering higher-quality inverted models with faster convergence. Additional benefits of IntraSeismic include its capability to integrate specific data constraints, offer uncertainty quantification, and act as a potential data compressor.