Gravitational wave inference with very long and complex waveforms can take months. Inference of large synthetic gravitational wave populations as required in scenario studies can also be months even years. The expensive runtime has been challenging for the measurements of astrophysical quantities such as Hubble constant and neutron star Equation of State, as well as studies of systematic effects on parameter estimation from detector noise, waveform modelling, inference pipelines, etc. In this e-seminar, I will introduce a Python-based reduced order quadrature building code named PyROQ and showcase its applications with the emphasis on the large speedup of parameter estimation without losing accuracy. With the runtime typically brought down from months to days, PyROQ can enable studies that are previously unscalable.