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Entangl

Find & resolve issues in data center engineering & operations using AI

Entangl uses AI to detect and automatically resolve issues in data center engineering and operations, ensuring efficiency and uptime.
Jobs at Entangl
San Francisco, CA, US
$120K - $170K
0.20% - 1.00%
1+ years
San Francisco, CA, US
$120K - $170K
0.20% - 1.00%
Any (new grads ok)
San Francisco, CA, US
$120K - $150K
0.50% - 1.00%
Any (new grads ok)
San Francisco, CA, US
$120K - $170K
0.20% - 1.00%
Any (new grads ok)
San Francisco, CA, US
$120K - $170K
0.20% - 1.00%
Any (new grads ok)
Entangl
Founded:2024
Team Size:3
Status:
Active
Location:San Francisco
Group Partner:Tom Blomfield
Active Founders

Shapol M, Founder

Co-founder & CEO at Entangl.

Antanas Zilinskas, Founder

Co-founder and CTO at Entangl.
Antanas Zilinskas
Antanas Zilinskas
Entangl
Company Launches
Entangl - Automating engineering design 🚀
See original launch post ›

tl;dr: We automate the detection of design errors in engineering projects and suggest solutions autonomously—saving time, money, and, potentially, lives.

—

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.

đź’˛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.

đź‘‹ Ask: How you can help

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