A leading background checking firm struggled with the manual processing of criminal court search documents, handling between 70,000 and 100,000 documents monthly. These searches required engaging with approximately 5,000 distinct court jurisdictions, each providing unique and varied response formats. The complexity and inconsistency of these forms made traditional automation impossible, forcing the firm to rely heavily on extensive manual data extraction processes, significantly inflating operational costs, resource demands, and turnaround times.
PressW designed and deployed an advanced AI-driven solution powered by Large Language Models (LLMs) that intelligently automated data extraction across the diverse range of court document formats. The AI effectively learned the distinct patterns and data structures inherent to each of the 5,000 unique form types, accurately identifying and extracting nearly 40 critical data fields automatically. This robust automation effectively removed manual bottlenecks, drastically streamlined document processing, and significantly boosted overall operational efficiency.