by Lauren Stone | Nov 27, 2024
Large-scale asset projects generate an overwhelming amount of data. From engineering drawings and equipment lists to preventive maintenance plans and Bills of Materials (BOMs), the sheer volume can feel unmanageable. Without the right strategies, this flood of... by Lauren Stone | Nov 22, 2024
Building Effective Human-in-the-Loop Frameworks for AI-Driven Data Extraction In the previous blog, we highlighted how combining human expertise with AI minimizes errors in industrial data extraction. Now, let’s break down practical ways to establish a... by Lauren Stone | Nov 20, 2024
Human Expertise and Data Extraction Industries are rapidly transforming as advanced tools streamline operations, including how data is extracted from technical diagrams, maintenance records, and other documents. From piping and instrumentation diagrams (P&IDs) to... by Lauren Stone | Nov 15, 2024
In the previous blog, we explored the many challenges that organizations face when extracting valuable information from technical tables. Manual extraction is tedious, prone to errors, and expensive, especially when dealing with high volumes of data. Fortunately,... by Lauren Stone | Nov 13, 2024
The challenges of extracting table data from technical documents are significant in industrial environments, where critical information is often embedded within dense, tightly packed tables. These tables may include parts lists, equipment specifications, material...