JuliaHub, a Cambridge-based Scientific AI startup, has raised $65 million in a Series B round led by Dorilton Capital, with participation from General Catalyst, AE Ventures, and technology investor Bob Muglia.
The funding announcement came alongside the launch of Dyad 3.0, JuliaHub’s new agentic AI platform focused on hardware engineering and industrial digital twins. The company says the product is designed to help engineering teams model, test, and validate complex physical systems across sectors including aerospace, automotive, utilities, and manufacturing.
The round highlights continued investor interest in AI applications beyond software, particularly in industrial and engineering workflows where simulation, controls, and physics-based modeling remain difficult to automate. JuliaHub, which builds AI-first tools for scientific and technical computing, is positioning itself at the intersection of scientific machine learning and industrial system design.
The funding announcement came alongside the launch of Dyad 3.0, JuliaHub’s new agentic AI platform focused on hardware engineering and industrial digital twins. The company says the product is designed to help engineering teams model, test, and validate complex physical systems across sectors including aerospace, automotive, utilities, and manufacturing.
The round highlights continued investor interest in AI applications beyond software, particularly in industrial and engineering workflows where simulation, controls, and physics-based modeling remain difficult to automate. JuliaHub, which builds AI-first tools for scientific and technical computing, is positioning itself at the intersection of scientific machine learning and industrial system design.