Senticore and Generative AI: Extracting Engineering Data from PDF

Senticore has developed a methodology to help manufacturing companies that regularly receive product assembly documentation/manuals in PDF format and must use that documentation for actionable and possibly collaborative steps.

That documentation contains instructions represented by text, tables, diagrams and drawings with PMI. Presently employees are either printing these instructions and distributing them to the shop floor stations, or they manually copy-paste some of that information into their MES/MRO system. This is a labor-intensive, error prone, and expensive process.

Senticore team has investigated a variety of options related to extracting information from PDF documents, and identified an approach with a rather high probability of success. Senticore calls it a generative AI infographics capture with a human in the loop. It allows extracting various data types from the PDFs and making them available for the MES consumption. 

That methodology allows training the AI from 20:80 to 80:20 human involvement within reasonable time. Also, as Senticore is aware about the traditional cyber concerns, the solution can be deployed locally on corporate premises, and integrated with other systems using REST API.

Senticore expects the customers to see significant business benefits out of this solution: increased efficiency and productivity – the process becomes significantly faster compared to manual extraction, with the system output continuously improving its overall quality, accuracy and consistency as the AI is learning more about specific documents layouts and elements.