Dexory taps SimScale AI to speed warehouse robot design

Dexory, a robotics and warehouse data intelligence company, has deployed SimScale's Engineering AI to help accelerate the design and testing of autonomous warehouse robots. The move builds on Dexory's existing use of SimScale's AI-native cloud simulation platform and adds new capabilities aimed at speeding up critical engineering workflows.

Under the new program, Dexory's engineers will use Engineering AI to identify the root cause of structural component failures more quickly, automatically explore multiple design variations through simulation, and create a searchable engineering knowledge base from previous projects. The platform automates several time-consuming tasks: it reduces the time spent investigating structural failures by enabling more simulation iterations during critical design phases, automates simulation reporting to make results easier to analyze and share, and allows engineers to automatically run parameter sweeps—testing multiple design variables simultaneously and generating comparative results without manual configuration. AI agents will also capture simulation knowledge from past projects to create a searchable engineering memory, helping teams reuse proven approaches and preserve expertise as the business grows.

The timing reflects broader industry pressure. As warehouse robotics adoption accelerates, engineering teams face increasing pressure to shorten product development cycles while maintaining performance and reliability. The global warehouse robotics market is projected to reach $117 billion（約19兆円） by 2034, up from $14.7 billion（約2.4兆円） in 2024, creating urgent demand for faster product development methods. Calum MacDougall, a senior mechanical design engineer at Dexory, framed the initiative as exploratory: "This pilot isn't just about solving today's engineering challenges. It's about understanding how AI will reshape engineering over the coming years and helping us discover where it can genuinely transform the way engineers work." Rather than focusing solely on productivity gains, the program is designed to help Dexory understand where AI agents deliver the greatest value across engineering and establish best practices for their future adoption. David Heiny, CEO at SimScale, noted that forward-thinking companies are already investing to understand how AI fits into their engineering workflows, and that Engineering AI has proven its ability to automate simulation tasks, explore significantly more design options, and help engineers make better decisions faster.

Dexory's decision to deploy Engineering AI reflects a wider shift in how manufacturers are approaching product development. While AI has already become central to the robots operating inside warehouses, the use of AI in the engineering processes that design and test those robots is still emerging. According to SimScale's CEO David Heiny, many engineering teams are still defining how AI will fit into their workflows, but forward-thinking companies are already investing to understand that fit quickly.

The scale of opportunity is substantial: with the warehouse robotics market projected to grow from $14.7 billion（約2.4兆円） in 2024 to $117 billion（約19兆円） by 2034, manufacturers face mounting pressure to accelerate product development without compromising on performance or reliability. Dexory's approach—using AI to reduce investigation time for structural failures, automate simulation reporting, and preserve engineering knowledge—directly addresses that tension. Rather than pursue productivity gains alone, the company is treating the pilot as an opportunity to learn where AI agents can genuinely reshape how engineers work, a mindset that may influence engineering practices across the broader robotics industry.

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