  Astrophysical transients with rapid development on sub-hour 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 followup. This paper presents the Evryscope Fast Transient Engine
(EFTE), a new data reduction pipeline 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
suited to continuously monitoring the transient sky at minute cadence.
Candidates are produced within the base Evryscope two-minute cadence for 98.5%
of images, and internally filtered using VetNet, a convolutional neural network
real-bogus classifier. EFTE provides an extensible, robust architecture for
transient surveys probing similar timescales, and serves as the software
testbed 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 62x higher than Evryscope.
