From pioneering digital tools like the open-source Buildings and Habitats object Model (BHoM) to redefining how we approach complex design challenges, we’ve pushed the boundaries of computational engineering. Now, we’re taking the next leap forward – investing in artificial intelligence and machine learning to unlock new levels of insight, efficiency and creativity across the built environment.
Machine learning is fast becoming a cornerstone of our computational strategy. It’s enabling us to solve complex challenges with greater precision and accuracy, from predictive modelling and generative design to sustainability analytics and operational optimisation.
In partnership with Birmingham City University, we’re launching a new Knowledge Transfer Partnership (KTP) role that will play a key role in this journey – developing bespoke algorithms and workflows that integrate seamlessly into our engineering and consultancy services, including the development of a drawing assistant through machine learning.
By using machine learning to transform engineering knowledge into actionable insights, we can deliver smarter, faster, and more informed outcomes for our clients.
What is machine learning?
Machine learning (ML) is a branch of artificial intelligence (AI) that enables computers to learn patterns from data and make decisions or predictions without being explicitly programmed for every scenario. Instead of following fixed rules, ML systems improve their performance over time as they are exposed to more data. In the context of the built environment, machine learning is increasingly being used to enhance design, construction, and operational processes.
Drawing assistance through machine learning
As machine learning continues to reshape how we design and manage the built environment, its potential becomes especially clear when applied to long-standing industry challenges. One example is navigating the vast, complex world of technical drawings. This is where Buro Happold’s in-house ML drawing assistant comes in: a practical application of AI tailored to the real needs of engineers, helping them extract insights from visual data and streamline workflows in ways that traditional tools cannot.
Technical drawings remain the primary format for sharing design information in the architecture, engineering and construction (AEC) industry. However, large projects often involve hundreds or thousands of drawings, making it difficult to locate relevant content or identify inconsistencies.
Drawings are visual data, and while existing AI software offer a variety of techniques to look at data and interpret this information, they often lack domain-specific knowledge and pose data privacy risks. To address this, Buro Happold is developing a drawing assistant with machine learning – a tool that uses AI to help find and interpret drawings more efficiently. Our in-house machine learning research and development is built securely and tailored to engineering workflows using our internal data.
The tool is already deployed on two major projects and currently focuses on text extraction, applying techniques like computer vision, natural language processing, and graph deep learning to extract metadata, identify symbols, and cross-reference annotations. Future enhancements include symbol recognition, compliance checking, drawing understanding using knowledge graphs, and a chatbot interface for natural language queries.
A platform for talent and impact
The development of our ML drawing assistant is just one example of how we’re applying advanced machine learning techniques to real-world engineering challenges. As part of this momentum, we are pleased to launch a new machine learning role in partnership with Birmingham City University through an 18-month Knowledge Transfer Partnership (KTP) – a UK government-backed initiative that bridges academia and industry to drive innovation and deliver real-world impact. Learn more about the KTP role and application process here.
The focus? To revolutionise how we interact with and extract value from technical engineering drawings and data – enhancing productivity, streamlining compliance, and unlocking new efficiencies across our engineering disciplines. These efforts are not only enhancing internal workflows but also laying the groundwork for broader innovation across the AEC industry.
We’re excited about the impact this new role will have in strengthening our team as we continue to foster a culture of collaborative intelligence and innovation, benefiting our clients, our partners and the built environment.
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