Detect errors in complex engineering projects using AI
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. 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). 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 2 months of work every year and makes engineering safer.
Active Founders
Shapol M
Co-founder & CEO at Entangl. Previously, I co-founded and led the Karman Space Programme at university. Under my leadership, we launched one of the most powerful British reusable rockets. I successfully grew the program, making it the best-sponsored program in Europe. Studied Master of Engineering (MEng) in Aeronautical Engineering at Imperial College London.
Antanas Zilinskas
Co-founder and CTO at Entangl. Previously led the engineering of a 25km reusable student rocket. Also co-founded an AI research lab at university focusing on humanoids, as well as trajectory predictions and flight readiness monitoring for rockets. Research experience at Tokyo Tech, simulating aerotrains using ANNs.
Company Launches
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 ⬇️).
🎉 The Solution: Autonomously detecting errors across an organization.
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.
💲Opportunity: Safer and quicker engineering
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
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