IndustrialMind.ai, an artificial intelligence (AI) company founded by former Tesla manufacturing AI team, announced Thursday a $1.2 million pre-seed round.
The firm said in a statement that investors in the round include Antler, Gang Song (angel; Ex-Tesla Vice President of Manufacturing), TSVC, and Plug and Play.
The funding will accelerate development and customer deployment of IndustrialMind.ai’s “AI Engineer,” with capabilities ranging from drawing-to-process automation
to real-time monitoring and root-cause analysis, improving yield, increasing throughput, and shortening new-product-introduction timelines.
Despite broad adoption of robotics and digital tools on the shop floor, converting data into timely operational decisions remains difficult — especially during rapid ramps and complex new-product launches.
Having built an AI manufacturing platform that solved critical bottlenecks at Tesla’s Giga factories, the founding team is now bringing that decision-making brain to the broader industry: an AI system that understands drawings and process data, recommends concrete adjustments, and helps validate impact on real equipment.
The effort focuses on rebuilding the decision-making center of modern manufacturing and redefining the factory of the future.
“Engineers already have enough tools. They need a real trustworthy teammate, an AI Engineer,
“The ultimate engineer on the factory floor combines manufacturing judgment with AI capabilities and delivers verified, actionable changes,” said Steven Gao, Co-founder， Chief Executive Officer of IndustrialMind.ai.
Gang Song, former Tesla VP of Manufacturing and the round’s angel investor, also said 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,” he added.
IndustrialMind.ai’s AI Engineer spans the path from print to performance.
It understands drawings to extract features and automatically draft BOMs, routings, and should-cost quotes, turning “drawing to process” into a minutes-long step.
On the line, it monitors production in real time, detects and predicts anomalies, and offers engineer-ready adjustments that keep processes stable and quality in control.
When issues arise, a multi-agent root-cause engine blends knowledge and data to surface fixes and auto-generate reports, closing the loop far faster than manual methods.
IndustrialMind.ai is already deploying the AI Engineer with industry leaders including Siemens, tesa, and Andritz, and operates a forward-deployed model that embeds the product directly into each customer’s workflows and systems to deliver measurable value within weeks.
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