Leaf Automation, a participant in Cohort 3 of Transform – a data science and AI startup accelerator powered by Deep Tech Ventures at the University of Chicago’s Polsky Center for Entrepreneurship and Innovation in collaboration with the Data Science Institute – is gaining recognition for its next-generation AI-enhanced CAD plugins.
The company, established by CEO and Cofounder Evan Haug, is committed to streamlining and optimizing the design of commercial electrical and mechanical systems. Haug emphasized the laborious nature of CAD drafting, which consumes a significant amount of an engineer’s time, hindering the pace of renewable energy infrastructure construction. In response to this challenge, Leaf Automation is integrating AI-automated design generation into CAD platforms, freeing up engineers to focus on more high-impact tasks.
By utilizing classical AI, reinforcement learning techniques, and rules-based guardrails, Leaf Automation aims to produce optimized and code-compliant engineering design schematics in a matter of seconds. Haug, with a background in electrical and solar engineering, emphasized the elimination of the need to acquire thousands of existing engineering drawings, resulting in models that achieve higher levels of optimization than those trained using human-generated design data.
The team is confident in the scalability of its reinforcement learning system and plans to expand across various engineering disciplines. With positive feedback from over 50 potential customers in the construction engineering industry, Leaf Automation seeks to harness the power of AI within CAD platforms for engineering design work.
Furthermore, Leaf Automation has joined forces with 10 companies to beta test its solar engineering automation tool for AutoCAD, Branch, scheduled for release in May of this year. Haug outlined the long-term vision of developing a suite of engineering automation applications across different disciplines, with the goal of releasing a new automation application each year and using the proceeds to support R&D into future and more ambitious automation applications.
As a part of the Transform accelerator, Haug expressed enthusiasm for collaborating with the Polsky Center’s resources to refine their commercialization plan, engage with UChicago AI/ML resources, and connect with construction engineering leaders to support ongoing work and future products. The assistance provided by Transform includes access to business and technical training, industry mentorship, venture capital connections, and funding opportunities.
Leaf Automation’s foray into the realm of AI-enhanced CAD plugins signals a promising future for the engineering industry, offering the potential to revolutionize traditional design and development workflows with state-of-the-art technology.
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