Foundation EGI, an AI engineering startup that spun from MIT, has officially been launched by Stealth with a $7.6 million seed round. The funds were led by the E14 Fund and Union Lab Venture, and were joined by Samsung Next, Grids Capital, Stata Venture Partners and Henry Ford III.
The company takes on one of the most overlooked problems in manufacturing. It’s a messy, manual engineering process that doesn’t meet the digital transformation seen in other industries.
Engineering General Intelligence (EGI)
Foundation EGI says it has built its first domain-specific AI platform focusing on General Engineering Information (EGI). The platform has already been tested with the Fortune 500 industrial brand. It is used there to clean up product design and development confusion.
The team is not short of pedigree. The company was co-founded by MIT researchers Mok Oh, Professor Wojciech Matusik and Michael Foshey. They put together a group of engineers and operators with deep experience in manufacturing, AI, and enterprise software.
The pitch is simple: turn ambiguous and distorted engineering instructions into clean, structured, machine-readable code. The platform is web-based and integrated with existing design and manufacturing software. Foundation EGI’s custom built large language models are trained exclusively for engineering and understand how physics, spatial logic, and physics products are actually created.
“Engineering is ready for an AI shift, but the general LLM is not built for this world,” CEO Mok Oh said. “We started with engineering documents and built domain-specific AI that translates messy documents into structured, accurate processes. Results: faster product cycles, fewer mistakes, significant cost savings.”
Why now?
Unlike other industries that employ digital transformation, manufacturing and engineering stay with outdated workflows. Instructions are often scattered across tribal knowledge, handwritten or buried, slowing down teams, introducing errors, and contributing to estimates of the basic EGI is more than $8 trillion in economic waste per year.
This is the Gap Foundation, which EGI aims to close.
The MIT spinoff builds a domain-specific AI platform that turns messy and inconsistent engineering instructions into structured, machine-readable code, bringing clarity, speed and accuracy to every stage of product development.
The core has a dedicated, large-scale language model trained specifically for engineering. In combination with the Agent AI platform, Foundation EGI takes natural language input – even if it is ambiguous or unstructured, it transforms into accurate, codified instructions. The web-based platform integrates directly with the key design and manufacturing tools already used by engineering teams, making adoption seamless.
By transforming Tribal Knowledge into a structured system, Foundation EGI brings automation and transparency to historically confused and inefficient workflows, helping teams move faster, reduce latency and build better products.
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Early users like global automotive supplier Inteva Products are already participating. “It’s clear that EGI can help eliminate unnecessary costs and automate disrupted processes,” said Dennis Hodges, CIO at Inteva.
Investors say the market timing is spot on. “Engineering and manufacturing have been pleading for this kind of AI solution,” said Habib Haddad, founding partner of the E14 fund. “The team, technology and market conditions make this an unusual opportunity to tackle the industrial bottlenecks of many years.”
Co-founder Professor Wojciech Matusik also shared the company’s vision on the TEDX MIT stage, explaining how EGI transforms natural language into engineering-specific instructions based on real physics. “This unleashes the creativity and speed of a new generation of engineers,” he said.
The startup foundation is built on years of research at MIT and other academic institutions. The work was entitled a large-scale linguistic model of design and manufacturing in a paper from March 2024, co-authored by Matusik, Foshey and others.
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