Case Study: Johnson Lambert LLP accelerates insurance audits with Provectus GenAI

Johnson Lambert streamlines the processing of reports by leveraging generative AI to extract and validate financial insights, empowering auditors to reduce time-to-audit by 50%

Johnson Lambert LLP, a CPA and consulting firm serving insurance clients, needed to speed up a manual audit workflow that involved extracting and validating financial data from unstructured PDF reports. The process was time-consuming, error-prone, and could take 60 to 80 hours per audit, limiting the firm’s ability to focus on higher-value client work.

Provectus helped Johnson Lambert LLP build a generative AI-powered report processing solution on AWS using Amazon Bedrock and Cohere’s Command LLM, with Amazon Textract and a flexible backend pipeline for extraction, normalization, and validation. The prototype was delivered in less than two months, and the solution improved audit efficiency by 20%, reduced document processing time by 50%, and significantly improved accuracy over manual methods.

Johnson Lambert LLP