tl;dr: We automate the detection of design errors in engineering projects and suggest solutions autonomously—saving time, money, and, potentially, lives.
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Hey folks, Shapol and Antanas here. We used to lead a reusable rocket program and oversaw the launch of four missions. We hated engineering design software so much that we created our own — which is why we’re here today :)
🧨 The Problem: Design errors get caught too late, resulting in delays or dangerous outcomes.
Organizations carry out design reviews every few weeks/months to ensure they catch errors early. As aerospace engineers, we've experienced firsthand the painful reality of cross-team design reviews. Teams grind for weeks to prepare for these meetings, yet costly errors still slip through to manufacturing or even operation (think doors blowing off planes).
The issue? Engineers work in silos, unaware of how their decisions impact the broader system. For example, changing the O-ring material might unexpectedly impact the seal integrity at low temperatures when building a space shuttle booster rocket (see NASA Space Shuttle Disaster below ⬇️).
Humans are terrible at dealing with large amounts of data and understanding how everything interacts with one another. Machines, on the other hand, are great! They can crawl across all the knowledge bases (GitHub, Google Drive, OneDrive, etc.) and detect changes as they are made.
Our platform identifies design problems autonomously across engineering projects. It then suggests targeted solutions to the right engineers and delivers daily insights and reviews, preventing expensive problems early on (poor engineering cost Boeing $100B+). This saves each engineer two months of work every year and makes engineering safer.
Engineers don’t need to spend two months a year grinding for design reviews. Your engineering projects don’t need to be delayed by an average of seven months. Prevent errors early to move faster and save your company’s runway.
👋 Ask: How you can help
We met whilst designing & launching rockets. Whilst doing that, we realised that we could automate a lot of our engineering design work with graph neural networks and transformer models. \Then we wondered if we could develop an AI system that can design any mechanical system (i.e. a car, rocket, etc). So, we started Entangl. We are creating an the smartest engineer ever!
We are creating an AI system that can design anything. Ambitious engineering projects—like space colonies and humanoid robots—haven't materialized yet. It's not due to a lack of money but because it's extremely difficult to assemble enough talented people to work together on them. Our aim is to transform this from being limited by human resources to something that is limited by computing power.