Code Ocean

About Code Ocean

Code Ocean provides a cloud-based computational research platform aimed at enhancing the reproducibility and efficiency of scientific discovery. Founded in 2014 by Simon Adar and Ram Dayan, the company originated from Adar's postdoctoral work at Cornell Tech, where he identified critical gaps in the tools available for computational science. Adar, with a background in signal processing and experience at the German Space Agency, teamed up with Dayan, who brought over 30 years of programming experience to build the platform. The company has secured significant funding, including a $16.5 million Series B round in May 2022, to fuel its growth and platform development.

The company's core offering is a Software-as-a-Service (SaaS) platform that functions as a digital lab for computational scientists. It primarily serves the biopharmaceutical, biotechnology, and academic research sectors, with clients like Sema4, Champions Oncology, and the Allen Institute. The business model centers on providing this integrated environment to standardize research workflows, manage data, and ensure that computational experiments are fully traceable and reproducible. This addresses a significant challenge in scientific research where results are often difficult to replicate due to variations in code, data, and computing environments.

The platform's central feature is the "Compute Capsule," an executable and shareable container that encapsulates the code, data, computational environment, and results of a research project. These capsules are version-controlled using Git and built on Docker technology, ensuring that an analysis will run identically every time, now or in the future. The platform integrates with common data science tools like Jupyter, RStudio, and MLflow, and operates on cloud infrastructure such as AWS, allowing researchers to provision necessary computing resources like CPUs and GPUs on demand. By automating infrastructure management and providing a collaborative space, Code Ocean enables scientists to focus on research rather than DevOps, ultimately accelerating the pace of discovery.