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...

How AI Can Help Recognize Custom Symbols in P&IDs

In this blog, we’ll break down how AI learns to recognize custom symbols, how these models adapt over time, and how they can be easily integrated into current engineering workflows to make handling P&IDs more efficient. AI is revolutionizing the way we...

Customizations in Engineering Diagrams: Navigating Variations

Each engineering project is unique, often requiring customizations beyond standard practices. Project teams frequently adapt or create new symbols and methods to fit specific needs, leading to variations even within the same organization. For example, in Piping and...

Embracing Automation – The Future of Data Extraction

Automation represents a pivotal shift in the landscape of data extraction, offering unprecedented efficiency and accuracy. This blog discusses the role of AI and machine learning in transforming data extraction processes, enabling industries to overcome the challenges...

Tackling Human Error in Data Extraction

Human error is a common issue in manual data extraction, often worsened by fatigue and the complexity of tasks. This blog examines the impact of fatigue-induced errors and explores strategies to minimize these issues, thereby improving data integrity and operational...