Reducing Inventory Check Errors by 99% Using AI-Driven Intelligent Order Intake

We implemented a fully automated, AI-driven system that read, interpreted, validated, and processed incoming part-related requests directly from email. The solution combined intelligent document processing, LLM-based understanding, and automated inventory integration to streamline the entire workflow end-to-end.

1. Intelligent Email Ingestion

   Incoming emails were automatically captured from the client’s shared inbox, with the system supporting the extraction of email body content as well as the reading and parsing of attachments in multiple formats, including XLS, XLSX, CSV, PDF, TXT, and others. It was capable of processing multiple attachments within a single email and interpreting complex tables and unstructured text to ensure accurate data handling.

2. AI-Based Interpretation of Part Requests

   A custom LLM pipeline analyzed the email content to identify part numbers, quantities, and additional instructions while accurately interpreting unstructured text. It validated the extracted data by removing irrelevant noise and detecting and ignoring non-relevant emails, thereby eliminating the need for manual review or formatting of incoming requests.

3. Real-Time Inventory Validation

   Once part details were extracted, the system automatically queried the client’s inventory system to perform instant lookups for the requested parts, validate the requested quantities, and classify the results as full matches, partial matches, or no matches.

4. Smart, Automated Customer Responses

   Based on inventory availability, the system triggered the appropriate response workflow to ensure efficient handling of each request. Irrelevant emails were automatically ignored without any human intervention, while requests with no matching parts resulted in an automated response informing the customer of unavailability. For full matches, a confirmation email with detailed availability information was automatically generated and sent to the customer.

   In cases of partial matches, the system autonomously sent a partial availability update to the customer and automatically raised a Purchase Order (PO) for the missing parts with the preferred vendor, ensuring minimal delay in fulfilling the request. This approach significantly reduced turnaround time across both request handling and procurement processes.

5. Centralized Logging and Analytics

   All system actions were comprehensively logged, including incoming email content, extracted part and quantity details, inventory match results, customer responses, generated purchase orders, and classifications of irrelevant emails. These logs enabled the client to generate actionable insights such as monthly performance reports, inventory demand trends, customer request patterns, and vendor dependency metrics.