Graph machine learning (ML) offers advanced methods for extracting insights from data, but its complex software ecosystem has created challenges for researchers, slowing progress and impacting developments such as lifesaving drugs. BSV was enlisted to assess the commercial viability of a no-code graph analytics web application that reduces barriers to entry for researchers, enabling them to utilise advanced graphical interpretation tools.

This platform democratises graph machine learning (ML) by offering a user-friendly interface that allows users to easily upload data, create datasets suitable for ML, and design sophisticated Graph Neural Network (GNN) architectures. The technology under review analyses complex graph-structured data, which is crucial in fields such as molecular property prediction, genomics, and drug discovery.