This project evaluated and optimized the client onboarding process for Electronic Data Interchange (EDI) integration networks to minimize lead-time variability and operational friction. Through data analysis, the team identified key inefficiencies in the legacy workflow, located the source of long-tail delays, and addressed data quality issues. To address these bottlenecks, the team designed a streamlined workflow featuring a pre-onboarding validation gate and parallel task execution. Additionally, they developed an AI-assisted automation architecture incorporating conversational outreach flows, automated error-code translation, and automated database record synchronization. These targeted optimizations aim to reduce overall process cycle times by 25–30%, lower rework rates, and save over 3,000 operational hours annually across client implementations.