BALER is a compression tool undergoing development at the particle physics division of the University of Manchester. BALER uses autoencoder and other types of neural networks as a type of lossy machine learning-based compression to compress multi-dimensional data and evaluate the accuracy of the dataset after compression. BALER is led by a collaboration of early-career scientists and welcomes all contributions.