This global auditing firm processes about 650 comfort letters annually, heavily relying on manual efforts. The client spent over 12,600 hours each year on manual processing, making searches for critical clauses slow and inefficient, limiting insights.

EdgeVerve AI Next’s Document AI automated extraction, reconciliation, and labeling. Utilizing NLP and machine learning, it quickly extracted key terms, allowing seamless PDF inputs and generating labeled documents. Advanced search and risk profiling minimized organizational risks.

Download the case study to discover how this was achieved.