Code Ocean

Code Ocean is a cloud‑based computational science platform that enables biotech and pharmaceutical researchers to build, share, and run reproducible analysis environments called Capsules, while providing built‑in data management, provenance tracking, and integration with existing cloud resources; pricing details are not listed publicly.

What it does

It enables users to define complete research workflows—from raw data ingestion through multi‑omics processing, imaging analysis, and machine‑learning model training—inside Docker‑based Capsules that capture the exact software stack, dependencies, and configuration needed for exact replication. The platform automates environment provisioning on AWS Batch, generates Dockerfiles on the fly, and records every step in a Git‑backed lineage graph, so results can be traced back to source code, input data, and compute parameters without manual bookkeeping.

Integrations with services such as AWS Batch, MLFlow, and nf‑core allow teams to plug existing pipelines and model‑tracking tools directly into the Code Ocean workspace. Users can import ready‑made bioinformatics pipelines from nf‑core with a single click, push model artifacts to MLFlow for versioned tracking, and scale compute jobs on demand through the cloud batch system, all while maintaining a single source of truth for data and model provenance.

Key features

• Capsules - Self‑contained, Docker‑based containers that bundle code, libraries, and runtime settings, enabling anyone to rerun analyses with identical results on any compatible cloud.
• Pipelines - Visual builder that lets users assemble multi‑step workflows, link Capsules together, and monitor execution status in real time.
• Data management - Central repository with custom metadata, controlled vocabularies, and FAIR‑compliant tagging that governs access and improves discoverability of large datasets.
• Lineage Graph - Automatic provenance map that records every input, parameter, and output, providing a full audit trail for regulatory review or collaborative debugging.
• ML model development - Integrated support for training, validating, and registering machine‑learning models, with direct export to MLFlow for downstream serving.
• Multi‑omics support - Pre‑built templates and tools for handling genomics, transcriptomics, proteomics, and metabolomics data within a single unified workflow.
• Imaging analysis - Built‑in utilities for processing high‑throughput microscopy or radiology images, including parallelized segmentation and feature extraction.
• Cloud management - One‑click deployment to AWS Batch, automatic shutdown of idle resources, and cost‑visibility dashboards that track compute usage per Capsule.
• Bioinformatics pipelines - Library of curated pipelines that can be customized or imported from nf‑core, reducing setup time for common sequencing analyses.
• Export & portability - Full Git export of Capsules and pipelines, allowing users to run the same environment on on‑premise clusters or alternative cloud providers without lock‑in.

Who it's for

The platform is aimed at computational scientists, bioinformaticians, and machine‑learning engineers working in biotech, pharmaceutical, and academic research settings. Typical users include senior data scientists, research software engineers, and principal investigators who need to collaborate across geographically distributed teams while meeting strict reproducibility standards. Organizations ranging from early‑stage biotech startups to large pharma enterprises—such as Allen Institute, Princess Margaret Cancer Centre, and Lantern Pharma—have adopted Code Ocean to replace ad‑hoc scripts and bespoke infrastructure with a shared, auditable environment.

Pricing

Code Ocean does not publish its pricing tiers on the public website, so interested organizations must contact sales for a customized quote. The company offers enterprise‑grade plans that include access to Capsules, Pipelines, data management, and cloud integration, with pricing typically structured around the number of users, compute consumption, and support level required.