Code Ocean Empowers Life Sciences with Secure, Scalable AI and Reproducible Research

Cloud computing has revolutionized the life sciences, providing researchers with unprecedented access to computational resources. However, effectively utilizing these resources requires specialized engineering and DevOps skills often beyond the core expertise of scientists. This gap creates challenges for research IT teams, who must balance infrastructure management, compliance, and enabling scientific discovery. As artificial intelligence (AI) innovation accelerates, these demands intensify, requiring robust IT governance to ensure secure and compliant AI implementation. Code Ocean addresses these challenges by providing a scalable, reproducible research platform designed to empower both research IT and scientists.

Scaling Research IT with a FAIR and Reproducible Science Platform

Code Ocean is a cloud-centered computational research platform that allows scientists to access cloud resources independently while maintaining security, compliance, and cost control. Deployed within a customer’s Amazon Virtual Private Cloud (Amazon VPC) endpoint, Code Ocean provides built-in access to data and scalable compute, freeing research IT from day-to-day support tasks. The platform automates cloud computing provisioning, enabling scientists to focus on research rather than infrastructure management.

At its core, Code Ocean integrates computational best practices. Code is automatically versioned with Git, ensuring every change is tracked and reversible. Analyses and pipelines are designed to be immutable and fully reproducible, guaranteeing results can be recreated exactly as originally generated. Data lineage is captured for every result, providing a transparent record of how outputs were produced. By using Code Ocean, data, analyses, and pipelines are automatically findable, accessible, interoperable, and reusable (FAIR). The platform supports commonly used tools like RStudio, Jupyter, Code Server, Nextflow, and MLflow, minimizing dependency on research IT. Built-in cost optimizations, such as automated storage tiering and idle compute resource shutdown, provide clear visibility into spending.

From Risk to Readiness with Trusted Agents

Organizations are increasingly exploring agentic AI to automate and accelerate scientific discovery. However, secure, compliant, and documented usage is crucial in regulated industries like life sciences. Code Ocean’s latest release, Trusted Agents in version 4.0, addresses these concerns by enabling research IT to provide secure, auditable AI access. Code Ocean provisions and manages AI infrastructure securely within the customer’s VPC, keeping sensitive data within their environment.

Code Ocean utilizes AWS Batch for workflow pipelines and system jobs and Amazon Elastic Compute Cloud (Amazon EC2) instances for system services and workers. This provides built-in guardrails for scientists to confidently use generative AI within a compliant framework.

Secure AI Infrastructure

Built on Amazon Bedrock, Code Ocean 4.0 leverages large language models (LLMs) such as Amazon Nova Pro and Claude Sonnet by Anthropic, and supports agents built using frameworks like Strands Agents. This allows developers and scientists to safely utilize the latest AI capabilities without compromising security or compliance.

Aqua: Trusted AI for Reproducible Science

The release introduces Aqua, a natural language AI agent designed specifically for scientists. Aqua combines the reasoning power of Claude Sonnet models with the ability to retrieve platform-specific knowledge and execute actions directly within Code Ocean. Using the Code Ocean Model Context Protocol (MCP), Aqua has 18 specialized tools for managing, searching, and executing tasks. Aqua ensures compliance and reproducibility through:

• Immutable data assets
• Code execution within Capsules for version control
• Full provenance tracking for AI-generated outputs
• User attribution for all actions

Cline: Secure Coding Assistance

For developers, the release introduces Cline, a secure, context-aware coding agent embedded directly into Visual Studio Code (VSCode). Preconfigured through Amazon Bedrock, Cline provides LLM-powered coding assistance within a familiar environment and enables integration of custom MCP servers into the Code Ocean platform.

Allen Institute Scaled Reproducible Research with Code Ocean

The Allen Institute, a Seattle-based research institute, adopted Code Ocean to address the need for a secure, reproducible research platform. Code Ocean accelerated their transition to AWS and provided scientists with access to a scalable computing environment. Researchers now consume over 1.75 million CPU hours and generate more than 150 TB of reproducible results each month. The institute has scaled its data processing from terabytes to petabytes annually using Code Ocean to manage scalability, cost controls, and compliance.

“Code Ocean makes it easy for our scientists to do their work reproducibly. Modern users to the platform can get far with just a little support; this gives our engineers time to focus on domain-specific challenges,” said Dr. David Feng, Senior Director of Scientific Computing at the Allen Institute for Neural Dynamics.

Over three years, the Allen Institute has generated a data corpus of over two petabytes on Code Ocean, running over 450,000 computations totaling over 1,500,000 hours. They now support over 250 researchers across disciplines with the part-time effort of only five research IT team members.

Code Ocean: The Trusted Foundation for AI-Driven Science

The convergence of cloud computing and AI presents both opportunities and challenges for life sciences organizations. Code Ocean bridges this divide, empowering scientists to innovate independently while allowing research IT to maintain governance and control. The Allen Institute’s experience demonstrates how research IT can support hundreds of researchers and petabyte-scale workloads through automation and easy access to scalable infrastructure.

Code Ocean Trusted Agents provides secure, auditable access to AI capabilities within an organization’s AWS environment. Aqua accelerates discovery with traceable and reproducible agentic analysis, and acts as a real-time support agent, diagnosing build issues and guiding users through workflows without IT intervention. This frees IT teams to focus on infrastructure scaling and scientific innovation, reducing operational costs and boosting self-sufficiency.

Code Ocean delivers a future where scientific breakthroughs are reproducible, researchers focus entirely on discovery, and AI accelerates the scientific process.

Book a demo or visit www.codeocean.com to learn more.

Code Ocean – AWS Partner Spotlight