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Product Spec Generator & Warehouse Data Automation Using AI & OCR

Client location: Germany

Our client, a leading player in the German industrial sector, runs an online shop and owns a warehouse dealing with thousands of machine parts. These parts often lacked standardized digital specifications, making warehouse management and Data population manual and inefficient.The warehouse staff had to manually look up the specs from the internet from the data sheet available from the part and update it in the ERP. This leads to delays in inventory updates and incorrect data.To manage this, we implemented an AI-powered middleware that integrates image recognition, OCR, and OpenAI (ChatGPT) to generate product specifications and sync them with the ERP system.

THE CHALLENGES

Standardizing and Automating Spec Generation from Physical Items

The core challenge was changing unstructured, often physical product information into structured digital data. Items arrived in the warehouse with either printed specs, labels, or none at all. Manual entry of specs from these physical documents into the ERP was time-consuming and error-prone.

  • OCR Accuracy: Extracting information from varying label formats (the labels, mostly engraved, were not super sharp at times or with very limited information) needed a robust OCR pipeline.
  • Contextual Understanding: Specs needed to be interpreted, not just read, requiring a language model to understand terms like material type, measurements, etc. The system had to generate all the required information for the product so that it’s ready to be listed in the online store.
  • ERP Integration: The final output had to be accurately mapped and sent to the ERP system with no/less manual intervention.
THE SOLUTION

AI-Powered Middleware for Image & Text-Based Spec Generation

We developed a comprehensive middleware system that automates the entire spec generation process:

  • Image Scanning & Identification: Warehouse staff scans items via a custom interface (A mobile app). The system uses AI-based image recognition to identify the type of part and match it with similar historical entries or collected details from the internet.
  • OCR & File Parsing: OCR is applied to any attached or scanned labels, PDFs, or images. It handles multiple file types (JPG, PNG, PDF) and extracts key attributes like part number, material, weight, brand, and available specs from the labels.
  • LLM-Powered Content Structuring: Using OpenAI's LLM, the extracted raw text is analyzed to generate standardized product specification sheets. The LLM ensures consistency in technical terms, unit conversions, and structure.
  • ERP Integration API: The structured data is automatically pushed to the client’s ERP via a secure API. A manual review is available if required. New items are created, and existing records are updated with/without manual touchpoints.
THE RESULT

Accelerated Warehouse Digitization & Inventory Management

With this solution in place, the warehouse team now enjoys a smooth and reliable spec generation process:

  • A 75% reduction in manual data entry related to new machine parts.
  • Over 90% accuracy in spec extraction and generation using OCR + LLM combo.
  • Real-time ERP updates reduce delays and ensure accurate inventory data.
  • Scalable architecture capable of handling increased load during stock inflow peaks.
  • Consistent product documentation, improving traceability, and compliance readiness.

This AI-powered transformation reduced operational inefficiencies. It also created a new level of agility and accuracy in warehouse and inventory management. By connecting physical products to digital workflows with AI, OCR, and LLMs, the client has built a smarter, faster, and future-proof warehouse infrastructure.

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