Polly Co-Scientist

Polly Co-Scientist is an AI-powered insights platform developed by Elucidata, designed to help biopharma R&D teams turn complex, multi-modal biological data into actionable insights. By combining customized dashboards, AI-assisted cohort builders, and a robust ML-ops infrastructure, Polly enables no-code data insight generation that is shareable with collaborators and reusable across different platforms — eliminating the fragmented workflows and scalability limitations that slow research progress.

The platform is purpose-built for life sciences R&D teams who need to perform seamless downstream analysis across large and complex datasets, including real-world evidence (RWE), omics, and other multi-modal data types. Polly delivers insights up to 4x faster while unlocking deep biomolecular knowledge from harmonized data, making it a trusted solution for leading biopharma organizations worldwide.

Core Problems Polly Co-Scientist Addresses

• Resource-heavy analyses and scalability challenges that slow research progress
• Insights that lack context or relevance to specific use cases
• Manual interventions in downstream analysis that reduce efficiency and consistency
• Fragmented workflows and complex data integration across multi-modal datasets

Key Platform Capabilities

• End-to-End ML-ops Infrastructure: Polly's robust architecture streamlines the entire machine learning lifecycle, from relevant data extraction using cohort builders, to cloud deployment and monitoring.
• AI-Assisted Text-to-Query: Enables no-code consumption of large and complex databases, allowing users to retrieve data without writing code.
• AI-Assisted Cohort Builders: Allows users to identify and analyze cohorts of interest, isolating and studying relevant data subsets. Cohorts can be saved and shared for reproducibility.
• Custom Dashboards: Tailored visualization applications enable in-depth exploration of trends and patterns, including cell-type composition and other biomolecular data.
• Multi-Modal Data Analysis: Integrated web applications support analysis and visualization across 25+ data modalities in real time, enabling seamless exploration across diverse datasets.
• Notebook and GUI Interaction: Users can interact with data through notebooks or a graphical user interface, supporting both technical and non-technical team members.
• Knowledge Graph Construction: Collaborate with domain experts to build knowledge graphs alongside custom dashboards and bioinformatics analyses.

Custom Solutions for Diverse Research Applications

• Patient stratification at scale
• Meta-analysis across large datasets
• Biomarker prediction and discovery
• Target identification
• Signature exploration
• Custom visualization apps and methods tailored to specific research needs

Platform Performance and Scale

• 30+ ETL pipelines built for multi-modality biological data
• 2M+ datasets processed and curated across projects
• 1,500+ samples per day processed and harmonized
• 10x faster harmonization powered by large language models (LLMs)
• 200+ multi-modal data products (each exceeding 10,000 samples) developed over the last five years

Measurable Outcomes

• 4x acceleration in insight generation using the cohorting tool
• 3x improvement in curation efficiency through custom-tailored metadata workflows
• 2x faster LLM model development and deployment, reducing time to insight
• 75% reduction in manual intervention through tailored automation, freeing up valuable research resources

Polly Co-Scientist is deployed on cloud infrastructure and is designed to integrate across the full data lifecycle — from curation and quality control to downstream consumption and visualization. The platform supports compliance and security requirements for enterprise biopharma environments and is trusted by leading global biopharma R&D teams across discovery, clinical research, precision diagnostics, and research informatics use cases.