One of our customers manages the complex task of sourcing thousands of individual parts from vendors around the world to build custom machines. Previously, their procurement process was manual and time-consuming—each request for quote (RFQ) had to be generated and sent out individually, with procurement staff tracking responses in spreadsheets or email threads. As design teams released new parts into the pipeline, the purchasing team often found themselves scrambling to keep up, which led to delays, inconsistencies, and difficulty comparing vendor quotes effectively.
To solve this, we developed a custom AI-powered procurement system that fully automates the RFQ workflow. As soon as parts are released from the design team, the system generates and sends RFQs to a pre-approved list of vendors based on the type of part and historical supplier performance. Each vendor receives a personalized email with a secure link to a web-based form where they can input pricing, lead time, and any relevant notes or conditions. This eliminates back-and-forth communication and ensures that all quotes are submitted in a structured, comparable format.
Once the vendor submissions are received, AI is used to analyze each quote in real time. The system evaluates delivery windows, cost efficiency, vendor reliability, and any special notes provided—such as expedited handling or discounts for volume. Based on a weighted scoring model tailored to the customer’s priorities, the AI recommends the optimal vendor and flags the quote for procurement approval. This approach has drastically reduced turnaround time for purchasing decisions, improved consistency across quotes, and empowered the business to scale its operations without adding procurement staff.