AI \ Case Study \ Revolutionizing Entity Extraction with Deep Learning for a Swiss-Swedish Electrical Equipment Company


Traditionally, electrical installation planning involves extensive manual drawings by civil architects. Depending on the size and complexity of the project, this process can take anywhere from two to four weeks. A heavy electrical equipment company, based in Switzerland and Sweden, was grappling with these challenges. The company was seeking to improve speed, flexibility, and overall efficiency of its design and bidding process for new prospects. However, it encountered several key challenges.

Key Challenges:

The electrical installation blueprints are intricate and often contain complex schematics that illustrate various electrical components such as lights, fans, wiring, cables, and other equipment. Civil architects need to painstakingly examine these drawings to prepare the component list required for the creation of the bill of materials and cost estimation. This process was time-consuming and prone to human errors.


Futurism, a coming-of-age AI technology solutions provider, presented a deep learning-based entity extraction solution using computer vision. This innovative solution interprets the electrical symbols on both scanned and electronic copies of building layouts, automatically identifying and classifying the various electrical components depicted in the blueprints.


The AI-driven solution was not only a game changer for the e-FAB (electronic Fabrication) business, but it also presented the following benefits:


Using advanced deep learning techniques, the solution automated the extraction of electrical symbols and corresponding equipment from the layouts. This significantly reduced the possibility of manual errors in the process.


The deep learning solution reduced the processing time dramatically. What once took 2 weeks, now took merely 2 hours. This signifies a staggering 168-fold reduction in time, thereby improving overall productivity by 400%.


With the capacity to extract entities from piping and instrumentation diagram (P&ID) diagrams, PDFs, images, and even videos, the solution greatly increased productivity. The company was able to respond to bids faster, with higher accuracy and consistency.

Statistical Impact:

Prior to the implementation of the solution, the company spent approximately 80-160 hours (2-4 weeks) per project just on the extraction and listing of components. Assuming an average of 3 weeks per project, the company spent roughly 4,680 hours a year on 30 projects.

With Futurism’s AI-driven solution, the time spent on each project was reduced to just 2 hours. Therefore, for the same 30 projects per year, the company would only spend 60 hours in total. This not only allows the company to take on more projects in a given year but also reallocate its resources more efficiently.

In conclusion, the deep learning-based entity extraction solution provided by Futurism has revolutionized the electrical installation planning process for the Swiss-Swedish electrical equipment company. By drastically reducing the time and effort required for electrical symbol extraction, the company has taken a giant leap forward in improving its productivity and operational efficiency.

Want to see how Futurism AI can revolutionize your operations?


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