Case Study - AI-Driven Credentialing Automation for Government

Overview

A leading U.S. government agency struggled with the high-volume credentialing of over 50,000 applications per month. Each submission included diverse document types such as IDs, photographs, and affidavits in both structured and unstructured formats (PDFs, JPEGs, PNGs). The manual processing of these documents was time intensive, error prone, and introduced compliance vulnerabilities. The agency needed a scalable, secure, and automated solution to streamline operations while ensuring data accuracy and regulatory compliance.

Challenge

A U.S. government agency faced a mounting challenge: processing over 50,000 credentialing applications per month each containing a variety of document types (PDFs, JPEGs, PNGs) with sensitive, structured and unstructured data. The manual review of IDs, photos, background checks, and affidavits was time-consuming, error-prone, and posed compliance risks.

Solution

We implemented a secure, AI-powered automation solution by integrating RPA with Azure Machine Learning and OpenAI GPT-4o. This hybrid approach streamlined end-to-end credentialing from intelligent document intake to human-in-the-loop approvals.

Benefits

• 53.5% Reduction in processing time
• 2.15x Faster processing
• 19.3% Annual Savings
• 50K+ Applications/month seamless automation