Electroencephalography hyperscanning enables the study of neural synchronisation during social interaction, but its application to adult–infant dyads in naturalistic contexts remains methodologically challenging. Developmental EEG is characterised by high artefact load and age-dependent signal properties, while hyperscanning requires harmonised preprocessing across partners to ensure valid inter-brain coupling measures. We introduce HyPICE, an open-source, end-to-end pipeline for adult–infant EEG hyperscanning that integrates adaptive developmental preprocessing with established hyperscanning analysis tools. HyPICE extends the use of APICE-Py (Automated Pipeline for Infants Continuous EEG, Lorenzo et al., 2025), for data-driven artefact handling, and (ii) HyPyP (Hyperscanning Python Pipeline, Ayrolles et al., 2021), for inter-brain connectivity analysis, into an improved unified system with a standardized architecture linking infant-specific preprocessing, inter-brain connectivity analysis, with BIDS-adapted organisation. HyPICE ensures consistent processing steps across dyad members while preserving individual signal characteristics. To improve the interpretability of neural synchrony in naturalistic interactions, this workflow also incorporates automated detection of mutual gaze events, enabling behaviourally informed analyses. With HyPICE, we offer a reproducible framework for multimodal integration, empowering researchers to explore neural synchrony in the context of naturalistic early social interactions.