Most engineering and design teams have a knowledge access problem. The critical data isn't in a neat text document; it's locked inside hundreds of technical drawings, blueprints, and schematics. Finding a specific material spec or part number often means manually opening files and visually scanning dense layouts, a process that hasn't changed in decades.

You can see a demonstration of the problem, and our solution, in this video: https://youtu.be/eh6JwPBAUI0

Off-the-shelf AI tools like Microsoft Copilot are built to parse text. They can summarize a Word document or find information in an email, but they fail when presented with a technical drawing. This is because the most important information in a blueprint isn't just the text itself, but its position and relationship to the visual elements-the lines, symbols, and projections that give it meaning.

The Logic for Reading Visuals

To solve this, we didn't try to force a text-based AI to understand an image. We built a system that specifically interprets the visual language of engineering documents. The core challenge is context. An AI needs to understand that a part number in a table on one side of the drawing corresponds to a specific component in an isometric view on the other.

Our approach focused on building the logic to connect these disparate pieces of information. The system learns to recognize not just characters and numbers, but also the common structures of technical drawings. It understands that certain symbols represent specific materials or that a leader line points from a dimension to the feature it describes. This allows it to answer questions that require synthesizing information from multiple points on the drawing, like "What is the finishing for part number A-74?"

We also prioritized security from the start. For teams handling proprietary designs, data privacy is non-negotiable. The entire system is designed to operate within a client's own secure Azure environment, ensuring their intellectual property never leaves their control.

Handling the Data

The system is now live. It processes entire libraries of multi-page drawing sets, making them fully searchable through a simple chat interface. Engineers can now ask direct questions and get precise answers with visual confirmation in seconds. The team no longer has to manually hunt through drawing sets to find specifications, part numbers, or material details. This fundamentally changes how they access and use their most valuable internal knowledge.