  We present an algorithm that allows fast and efficient detection of transits,
including planetary transits, from light-curves. The method is based on
building an ensemble of fiducial models and compressing the data using the
MOPED algorithm. We describe the method and demonstrate its efficiency by
finding planet-like transits in simulated Pan-STARRS light-curves. We show that
that our method is independent of the size of the search space of transit
parameters. In large sets of light-curves, we achieve speed up factors of order
of $10^{8}$ times over the full $\chi2$ search. We discuss how the algorithm
can be used in forthcoming large surveys like Pan-STARRS and LSST and how it
may be optimized for future space missions like Kepler and COROT where most of
the processing must be done on board.
