We propose a monolithic implementation of a feed-forward neural network in AlGaAs/GaAs waveguide material with a Wannier-Stark superlattice in the core. Adjustable weights are applied with the use of voltage-controlled below-bandgap intensity modulators. Nonlinear thresholding is performed with the use of a saturable absorber component. A 2-to-1 single neuron device was fabricated by integrating two 25 dB/mm modulators and a 25 dB nonlinear switch. The device performed with an output/input range ratio of 25 dB using two 780 nm laser diodes.