Moonglow — Connecting local Jupyter notebooks to remote cloud compute.
Location: San Francisco, CA, USA
Industry: B2B -> Engineering, Product and Design
Tags: Artificial Intelligence, Developer Tools, Machine Learning, DevOps, Infrastructure
YC batch: S24 | Status: Active | Team size: 2
Former names: Kopfkino

Moonglow connects local Jupyter notebooks to remote cloud compute. Machine learning researchers and data scientists use us to scale up their experiments without having to do DevOps.

Previously, Leila was a software engineer at Jane Street. She led the build-out of its equities clearinghouse connectivity infrastructure and was the technical lead of its front-office SRE team. Trevor was part of Hazy Research Lab at Stanford, and published machine learning research at ACL and ICLR.

With the explosive growth of deep learning, there are over 1 million ML researchers who do computationally intensive experiments every day. They use Jupyter notebooks to do so, but every time they want to try out a new idea, they need to get the notebooks running on cloud machines. This process, repeated hundreds of times a month, is time-consuming and error-prone.

Moonglow reliably brings the time-to-experiment down from 5 minutes to 20 seconds. Just as Vercel and Replit abstracted away the lower levels of the computing stack for web developers and programmers, we do the same for ML researchers.

https://moonglow.ai