Coiled

Coiled Computing, Inc. operates as a lightweight compute platform tailored for Python data engineers and scientists, enabling them to scale workloads to the cloud without requiring expertise in Docker or Kubernetes. The company was founded in 2020 by Matthew Rocklin, the original author of Dask, a popular open-source library for parallel computing in Python. Rocklin, who holds a PhD in computer science from the University of Chicago, previously developed Dask while at Anaconda and later led the Dask team at NVIDIA before establishing Coiled to address the deployment challenges organizations faced when trying to scale Python workflows.

The company's core product, Coiled Cloud, is a managed, Dask-as-a-service platform that allows users to spin up and tear down large clusters of cloud machines directly from their Python code with a simple API. This approach is designed to minimize development friction and reduce costs by eliminating idle resources. Key features include automatic environment synchronization, which replicates a user's local Python environment on remote machines without needing to build Docker images, and detailed telemetry for monitoring both system and Python-level performance. The platform supports multi-cloud deployment across AWS, GCP, and Azure, providing flexibility and avoiding vendor lock-in. Coiled serves data professionals, scientists, and researchers for tasks ranging from data manipulation and spatial analysis to AI and machine learning. Notable clients include Capital One and Anthem Health.

Coiled's business model is rooted in its open-source origins, offering a commercial product that makes Dask enterprise-ready. Revenue is generated through a tiered subscription model based on compute usage, with enterprise contracts forming a significant portion. The company offers a substantial free tier to encourage adoption and experimentation. After its inception, Coiled secured $5 million in a seed round in September 2020, co-led by Costanoa Ventures and IA Ventures. This was followed by a $21 million Series A round in May 2021, led by Bessemer Venture Partners, bringing the company's total funding to $26 million.

Keywords: parallel computing, Dask, Python scaling, big data, data science platform, cloud computing, machine learning infrastructure, serverless functions, data engineering, cluster management, Matthew Rocklin, distributed computing, cloud cost management, Python API, GPU computing, enterprise data science, workflow orchestration, ETL pipelines, scientific computing, remote development