Case Study: Leading Car Manufacturer achieves automated, transparent requirements analysis with Cortical.io Semantic Search

How a Leading Car Manufacturer Automated Its Requirement Analysis Process

Leading Car Manufacturer was struggling to manage and compare a growing corpus of specification documents—thousands of sheets totaling over 150,000 individual requirements—where similar requirements were written in many different ways, buried in tables, or too short for conventional search. Previous automation attempts failed, so the company engaged Cortical.io and its Cortical.io Semantic Search capability to automate requirement analysis and improve cross‑project transparency.

Cortical.io implemented a solution that ingested and sliced documents, extracted table data and requirement fragments, created semantic fingerprints, compared and grouped semantically similar requirements, and exposed the results via a web interface. The Cortical.io system processed over 150,000 requirements and, against a Gold Standard, achieved 88% recall and 96% precision—allowing engineers to compare specifications across projects, eliminate duplicates, standardize formulations, and reliably identify project‑specific versus generic requirements.