Dexory has deployed SimScale's Engineering AI to accelerate the design and testing of autonomous warehouse robots, a move that comes as the global warehouse robotics market is projected to grow from $14.7 billion to $117 billion over the next decade. Engineering teams now face mounting pressure to deliver products faster without sacrificing performance or reliability.
The robotics and warehouse data intelligence company already uses SimScale's AI-native cloud simulation platform. The new Engineering AI program adds three capabilities: faster root-cause analysis of structural component failures, automated exploration of design variations through simulation, and a searchable knowledge base built from previous engineering projects.
How the engineering workflow changes
Engineers will run more simulation iterations during critical design phases, reducing the time spent investigating structural failures. The platform automates simulation reporting so results are easier to compare and share across teams. Parameter sweeps - testing multiple design variables simultaneously - will run automatically, generating comparative results without manual configuration.
AI agents will also capture simulation knowledge from past projects to create what the company calls a searchable engineering memory. This helps teams reuse proven approaches and retain expertise as the business grows.
Beyond productivity metrics
The program is designed to do more than cut engineering hours. Dexory wants to identify where AI agents deliver the most value and establish best practices for future adoption. Calum MacDougall, senior mechanical design engineer at Dexory, described the challenge: "AI has a 'blank sheet of paper' problem in engineering because we're still discovering where it can create the greatest value."
MacDougall added that the pilot is not only about solving current engineering problems. "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."
Dexory's program reflects growing interest in AI for Product Development across manufacturing, where companies are embedding AI into the processes used to design, simulate and optimise physical products. David Heiny, CEO at SimScale, said industry research shows many engineering teams are still defining how AI fits into their workflows, but "forward-thinking companies are already investing to build that understanding fast."
Heiny said Engineering AI has already demonstrated its ability to automate simulation tasks, explore more design options, and help engineers make better decisions faster. "By piloting these capabilities broadly today, companies like Dexory are helping shape the future of their engineering practices."
Why this matters for product development professionals
The Dexory-SimScale program signals a shift in how engineering teams approach AI adoption. Rather than chasing immediate productivity gains, the focus is on running structured experiments to learn where AI agents deliver measurable returns. For product development leaders, this means the near-term opportunity lies in building internal knowledge about AI's engineering applications - not in buying a single tool that promises to fix everything. Companies that wait for perfect clarity risk falling behind competitors who are already running these experiments and capturing the institutional knowledge that comes from them.
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