Abstract Astrophysical transients with rapid developments on subhour timescales are intrinsically rare. Due to their short durations, events like stellar superflares, optical flashes from gamma-ray bursts, and shock breakouts from young supernovae are difficult to identify on timescales that enable spectroscopic follow-up. This paper presents the Evryscope Fast Transient Engine ( EFTE ), a new data reduction pipeline that is designed to provide low-latency transient alerts from the Evryscopes—a north–south pair of ultra-wide-field telescopes with an instantaneous footprint covering 38% of the entire sky—and tools for building long-term light curves from Evryscope data. EFTE leverages the optical stability of the Evryscopes by using a simple direct image subtraction routine that is suited to continuously monitoring the transient sky at a cadence of a minute. Candidates are produced within the base Evryscope 2 minute cadence for 98.5% of images, and internally filtered using vetnet , a convolutional neural network real–bogus classifier. EFTE provides an extensible and robust architecture for transient surveys probing similar timescales, and serves as the software test bed for the real-time analysis pipelines and public data distribution systems for the Argus Array, a next-generation all-sky observatory with a data rate 62 times higher than that of Evryscope.