Biomedical researchers face a critical productivity gap when working within Trusted Research Environments, where strict security rules ban the use of Large Language Models (LLMs). To solve this, we present the Trusted Agentic Environment, designed to embed AI tools and make them available to researchers by default. By attaching flexible, automated policies directly to datasets, researchers can seamlessly leverage LLMs for code generation, data exploration, and statistical modeling. This integration unlocks complex co-analysis, empowering researchers with advanced AI capabilities to accelerate their scientific output.
Biomedical researchers face a critical productivity gap when working within Trusted Research Environments, where strict security rules ban the use of Large Language Models (LLMs). To solve this, we present the Trusted Agentic Environment, designed to embed AI tools and make them available to researchers by default. By attaching flexible, automated policies directly to datasets, researchers can seamlessly leverage LLMs for code generation, data exploration, and statistical modeling. This integration unlocks complex co-analysis, empowering researchers with advanced AI capabilities to accelerate their scientific output.