The patented system, officially titled "Method And System For Identifying Hierarchical Relationships Between Data Elements Of Document," moves beyond traditional processing methods. By utilizing a neural network capable of analyzing both textual and visual modalities, the engine automates data extraction from highly variable files. This allows Dociphi to interpret nested form fields, tables, and sub-sections with high accuracy.

Arunima Gautam, product owner of Dociphi, noted that the patent validates the platform’s ability to handle complex records such as policies, endorsements, and claims with deeper contextual awareness. Srikant Venkatesh, Quantiphi’s global head of BFSI, added that the innovation provides banking and insurance organizations with a tool to manage intricate workflows more reliably. By removing the dependency on manual templates, the company aims to help enterprises unlock data value more efficiently across document-intensive operations.