Accurate Text Extraction from Charts
and Tables with Prompt Engineering

We developed a robust solution to address the problem of fast and accurate data extraction from complex charts and tables in PowerPoint and PDF documents. We employ prompt engineering techniques and utilize Claude 3.5 Sonnet, a state-of-the-art language model, to automatically identify and extract text and numbers from all visual formats. Our approach combines sophisticated NLP and ML to provide high accuracy and efficiency. By implementing this solution, construction firms can automatically extract critical information from their project documents, allowing them to make decisions more quickly and inform, allocate resources more effectively, and improve the accuracy of their project estimates. This focused approach will improve project results, making companies more competitive within the fast-paced construction industry.