The media relations person found me somehow tempting with this teaser:
- Converting natural language into code – Transform vague or unstructured instructions into precise, actionable code through AI-driven natural language processing.
- Enhancing automation, accuracy, and efficiency – Minimize manual input and errors, optimizing every stage of the design-to-production lifecycle with intelligent automation.
- Seamlessly integrating with existing tools – Leverage AI to integrate effortlessly with existing design and manufacturing software, ensuring full compatibility with established engineering tech stacks.
OK, this is general, full of the latest buzz words. Reading between the lines of this and her emails, I thought I detected the seeds of an answer to problems I had working in engineering data management in the late 70s. So, I consented to an interview (I do few of these anymore) with Foundation EGI co-founder Wojciech Matusik, Professor of Electrical Engineering and Computer Science at the Computer Science and Artificial Intelligence Laboratory at MIT.
This decision was one of my best lately. Matusik laid out a coherent, logical, precise definition of what this company (that launched last week) defines as the problem and the solution it intends.
These are my words—I see what they are doing as the crucial step between PLM and MES. That’s a bit to crude, but bear with me.
Early in my career, the VP of Product Development for a manufacturing company picked me for the role of data manager. From the foundation of managing the bills of materials and specifications generated by product design communicating with other departments such as manufacturing operations, cost accounting, and purchasing. These placed me at the center of cost control and reduction efforts (Hello, Elon, I could have helped you do a better job!).
Matusik began with the premise that engineering is programming, that is, it generates a set of rules in a domain-specific language. Look at assembly, for example, it is a small set of operations from a small domain. From this, one could construct a domain-specific program for any set of tasks. (I call this workflow—something I’ve seen MES developers trying to perfect for more than a decade.)
A coding assistant would be a great help developing these task programs. AI helps today’s software engineering become more efficient. Why not use the same tools for this problem? Enter Foundation EGI. Natural language programming of these “rules” for building from the engineering design data.
- Construct domain
- Program compilers
- Data Sets
- Then use LLMs and so forth
They are building a platform. Engineering change notices built-in. Focus on the most boring of engineer’s work, leave to the engineer the most creative. They hate the add-on administrative work. They integrate with a variety of CAD files and works either with PLM or not. Also fits well with robotics with automated coding assistant.
Like I have told a few founders whom I’ve interviewed, I am enthusiastic about the potential of your platform—I’m interested in seeing how the technology actually works out.
On Thursday, April 17, Foundation EGI launched, announcing the availability of the first domain-specific, agentic AI platform — engineering general intelligence (EGI) — designed to supercharge automation, accuracy, and efficiency for every stage of product lifecycle management. With EGI, design and manufacturing engineers will be able to build better products faster, driving healthier revenues for the world’s leading industrial brands. To sign up to be part of the beta, interested customers can sign up here.
Foundation EGI was co-founded by MIT academics Mok Oh, Ph.D, Professor Wojciech Matusik, and Michael Foshey, and has assembled a seasoned team with deep engineering, industrial, startup and AI experience. Backed by an over-subscribed $7.6M seed round from early investors including E14 Fund, Union Lab Ventures, Stata Venture Partners, Samsung Next, GRIDS Capital, and Henry Ford III, Foundation’s EGI platform is already in testing at leading Fortune 500 industrial brands, which are witnessing its transformative and revenue-driving potential.
Unlike other digitally-transformed industries, manufacturing and engineering processes and instructions remain manual and disorganized, causing inefficiencies, production delays and stagnant revenues — to the tune of $8T in economic waste. Using Foundation EGI’s purpose-built large language model (LLM) and EGI agentic AI platform, engineers can now transform natural language inputs, including vague and messy instructions, into codified programming that is accurate and structured, optimizing automation, accuracy and efficiency at every stage of the design to production lifecycle. Foundation EGI’s web-based technology platform seamlessly integrates with the major design and manufacturing software applications and tech stacks already used by engineering teams.
“Engineering is primed for an AI revolution, but generic LLMs won’t cut it: they lack vital domain-specificity and are prone to inaccuracies,” said Foundation EGI co-founder and CEO, Mok Oh. “Our first-of-its-kind technology is purpose-built for engineering and will supercharge every stage of product lifecycle management — starting with documentation. EGI transforms what is traditionally error-prone, manual and inconsistent into structured, sustained and accurate information and processes, so that engineering teams can not only achieve significant cost-savings but also be more nimble, productive and creative.”
Dennis Hodges, CIO at Inteva Products, a global automotive supplier of engineered components and systems, commented: “We have high expectations from Foundation’s EGI platform. It’s clear it will help us eliminate unnecessary costs and automate disorganized processes, bringing observability, auditability, transparency and business continuity to our engineering operations.”
Said Habib Haddad, founding Managing Partner of the E14 Fund, the MIT Media Lab affiliated venture fund: “The timing and market conditions are perfect for a company like Foundation EGI to solve what has long been a large and expensive challenge for America’s industrial manufacturing leaders. The combination of Foundation EGI’s vision, its world-class team, the widespread industry appetite for enterprise AI solutions, plus the uptick in manufacturing demand makes this a rich opportunity.”
Co-founder Wojciech Matusik, Professor of Electrical Engineering and Computer Science at the Computer Science and Artificial Intelligence Laboratory elaborated on EGI’s potential, “Engineering general intelligence transforms natural language prompts into engineering-specific language using real-world atoms, spatial awareness and physics. It will unleash the creative might of a new generation of engineers. Expect leaps and bounds in agility, innovation and problem-solving.”
Foundation EGI’s mission was inspired by research conducted by Professor Matusik, Michael Foshey, and others at MIT and other academic institutions, published in a March 2024 paper titled “Large Language Models for Design and Manufacturing.”
