MARIE

Unlike traditional large language models that function as passive, text-based chat assistants, a scientific AI agent possesses the capacity for autonomous execution. Built explicitly to advance agentic AI for science, these systems use native tool integration, short- and long-term memory structures, and advanced reasoning loops. This approach allows them to connect to multiple apps, navigate enterprise databases, and execute multi-step workflows without step-by-step human prompts, serving as active digital partners for scientists and researchers.

Modern platforms shift laboratory workflows from traditional science to agentic science. Historically, researchers have spent substantial manual effort bridging disconnected software silos, managing data ingestion, and preparing datasets. By automating data orchestration across an entire enterprise, agentic solutions eliminate procedural bottlenecks, accelerating project timelines and allowing scientists to focus on new data interpretation. 

MARIE fundamentally changes scientific research by transforming static, isolated documentation into dynamic assets. MARIE accesses both new data generated at the laboratory bench and historical data stored on the 3DEXPERIENCE platform. By accessing all these digital records, MARIE surfaces potentially hidden data to enable enhanced, automated knowledge-sharing. The connected nature of the data also means regulatory, quality, and computational teams constantly operate from a single, verified, and continuously synchronized source of truth.

Advanced computational models can suggest novel hypotheses by ingesting new data streams from internal proprietary repositories and public literature reviews. Specialized artificial intelligence then analyzes cross-disciplinary data patterns to screen variables, predict molecular properties, and evaluate feasibility. This approach provides a prioritized matrix of high-probability leads before scientists invest resources into physical experimental design. 

Advanced systems compress the timeline of scientific discovery by removing administrative and compliance-related friction from the innovation lifecycle. In the domain of Agentic AI for scientific research, MARIE can compile documentation, suggest future experimental directions and draft regulatory dossiers. By generating content from trusted scientific sources, with a detailed understanding of scientific models and rigorous standards, all while keeping the scientist in the loop, MARIE's AI outputs significantly reduce the time required to advance a molecule from early discovery to market approval.

An AI agent does not replace human oversight or function as an autonomous decision-maker; final accountability in highly regulated GxP environments must always remain with qualified professionals. MARIE serves as intelligent, human-in-the-loop orchestration Virtual Companion that simplifies the workloads of QA and regulatory teams. By securely navigating enterprise data silos, MARIE accelerates document assembly for complex regulatory submissions like CMC dossiers and APQRs, enforcing absolute traceability with an unalterable audit trail within the secure 3DEXPERIENCE platform. MARIE can also monitor global regulations and identify compliance gaps before they become risks.