BCI-FIT is a customization protocol dataset for non-implantable communication brain-computer interface (cBCI) systems, comprising EEG recordings from five participants with speech and/or physical impairments due to amyotrophic lateral sclerosis (ALS). Participants completed calibration and copy-spelling tasks using both customized and non-customized versions of a cBCI system across multiple visits, with iterative system adjustments based on performance, preferences, and signal characteristics. The dataset includes EEG data collected using dry electrode caps (DSI-Flex or DSI-24) sampled at 300 Hz during Matrix and RSVP typing paradigms.