Background: 

A vibrant and quickly growing organization in the sphere of research services. Specialties include Synthetic Organic Chemistry, Scale-up, Medicinal Chemistry Building Blocks, and Reagents. They operate in the San Francisco Bay Area and beyond, focusing on quality and timely delivery to help their customers complete their work in today’s fast-paced discovery research climate. Assistance in acquiring commercial intermediates from our global supplier network.  

They are facing significant challenges with their existing order management system, which relies heavily on emails and Excel-based tracking. The manual process was not only time-consuming but also prone to errors, leading to inefficiencies in tracking orders through various stages of the order processing lifecycle. 

Objective: 

The organization required an intelligent order management solution that could automate the processing of inbound emails with attachments based on lifecycle requirements and enable seamless contact with external entities via automated email notifications. 

Solution: 

To address these challenges, an Artificial Intelligence (AI) based email processing solution was implemented. This innovative solution offered several key features: 

Automated Email Classification: The AI system automatically classified incoming emails and processed data contained within attachments, significantly reducing manual data entry efforts. 

Order-Centric Analytics: The solution provided tailored analytics, insights, recommendations, and predictions based on individual orders and order items. 

Simplified Communication: External entities could send emails without traditional login processes, streamlining the communication flow. 

Email Alerts/Notifications: Automated alerts and notifications kept the process simple yet effective, ensuring that stakeholders were informed in real time.  

Scalability: Designed with future growth in mind, the solution could easily accommodate new enhancement requests. 

Implementation: 

The AI-based system utilized IMAP protocol to receive emails from various stakeholders, such as SCM (Supply Chain Management), vendors, freight forwarders, and clearing agents. A rule-based email-bot (AI) is deployed to classify incoming emails by their content and attachments. The SMTP protocol was employed to send out responsive emails with the necessary documents attached. 

Data extracted from PDF attachments were stored in MongoDB databases. A web application and dashboard were set up to allow manual overrides when necessary and to monitor order history. This setup also provided valuable insights, recommendations, and predictions to further enhance order management.