Extracting Data from Scanned Images and Paper Drawings

Extracting data from scanned images and paper drawings is a major challenge for industries that rely on technical diagrams. These formats make it difficult to access information, requiring engineers to manually search through non-searchable documents to find specific tags, symbols, or line numbers—a slow and error-prone task.

The inconsistency in diagram formats and varying resolution qualities further complicates the process, making it tough even for advanced optical character recognition (OCR) systems to provide accurate results. As a result, manual data extraction is still common, leading to inefficiencies and delays.

Moreover, as the volume of these legacy documents grows, the task of managing and extracting data becomes increasingly overwhelming. Without an efficient solution, teams may find themselves dedicating significant time and resources to a process that could otherwise be streamlined, which can have a direct impact on project timelines and costs.

AI-driven solutions are transforming this process. By using AI to automatically recognize and extract relevant symbols and text, these tools greatly speed up data extraction while reducing the risk of errors.

How Can We Help You?  

HubHead and DataSeer’s AI Service combines human-level understanding with machine speed to build a scalable knowledge data store of engineering designs. By integrating these solutions with your existing EAM/CMMS systems and creating a digital twin, you can enhance decision-making and streamline your maintenance processes. Contact us for a free demo or book a call.  

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