Singapore-based startup IndustrialMind.ai has secured US$1.2 million in pre-seed funding to advance its mission of transforming factory operations through artificial intelligence. The round was backed by early-stage investors Antler, Plug and Play, and TSVC, alongside angel investor Gang Song, former Vice President of Manufacturing at Tesla.
Developing an AI assistant for engineers
IndustrialMind.ai, founded by former Tesla manufacturing AI leaders, is building an “AI Engineer” designed to improve operational decision-making across global manufacturing floors. The system supports functions such as drawing-to-process automation, real-time monitoring, and root-cause analysis. These capabilities aim to improve production yield, increase throughput, and accelerate new product introduction.
Despite widespread adoption of robotics and digital systems, many manufacturers still face challenges in converting complex production data into timely, effective decisions. IndustrialMind.ai seeks to bridge that gap with an AI platform capable of interpreting engineering drawings and process data, recommending precise operational adjustments, and validating their impact on real equipment.
“Engineers already have enough tools. They need a real trustworthy teammate, an AI Engineer. The ultimate engineer on the factory floor combines manufacturing judgement with AI capabilities and delivers verified, actionable changes,” said Steven Gao, Co-founder and CEO of IndustrialMind.ai.
Gang Song, former Tesla executive and angel investor in the round, added, “This is a rare team that understands both high-volume manufacturing and state-of-the-art AI. IndustrialMind.ai has solved real bottlenecks on real lines. IndustrialMind.ai is bringing that playbook to the broader industry.”
From drawings to production performance
IndustrialMind.ai’s AI Engineer offers end-to-end assistance, covering the journey from design to production. It interprets engineering drawings to automatically generate bills of materials, routing plans, and cost estimates, turning what used to be a lengthy “drawing-to-process” step into a matter of minutes. On the production line, it continuously monitors operations, identifies anomalies, and provides actionable recommendations that help engineers maintain stable and efficient processes.
When issues arise, the platform’s multi-agent root-cause engine combines data analysis with expert knowledge to diagnose problems, propose solutions, and automatically generate reports. This process significantly reduces the time and effort required for troubleshooting compared to traditional manual approaches.
Early adoption and global partnerships
IndustrialMind.ai has already begun deploying its AI Engineer with established industry players such as Siemens, tesa, and Andritz. Its “forward-deployed” model integrates the platform directly into customer workflows, allowing teams to achieve measurable results within weeks of implementation.
The company’s approach builds on the founders’ experience at Tesla, where they developed an AI manufacturing platform to address critical bottlenecks in Gigafactory operations. IndustrialMind.ai now aims to make similar intelligent decision-making tools accessible to manufacturers worldwide, positioning AI as a core driver of efficiency, quality, and innovation in industrial production.
