Accelerate research by integrating data from public repositories with proprietary datasets. With Polly, scientists have access to clean, curated biological data on a single platform, minimizing the need to switch contexts between interfaces.
Reduce the time-to-analysis by 70% with Polly's curated data available in standardized machine-readable formats. Scientists can streamline downstream analyses with enhanced conformity and superior data quality due to the pre-processing of data in ETL pipelines.
Scientists often need to process multi-omics, bio-assays, clinical, EHR, and other forms of data stored in heterogeneous systems within their organization or sourced externally. Polly's scalable infrastructure consolidates and standardizes data, breaking silos and allowing teams to access data asynchronously.
Data custodians can save time on data wrangling and empower biologists with the data they need for faster analysis. Use rich annotations and ontology-backed metadata to query millions of datasets.
Scientists can spend less time managing data and more on science, using stored and versioned data on Polly. With centralized data acquisition, management, and harmonization in Polly, scientists can focus on research instead of data wrangling.
Polly's proprietary curation models drive ML readiness across 1.4 million datasets.
Samples curated across 32 sources.
Data points to form relationships over curated metadata.
Auto-curated entities, allowing researchers to create richer knowledge graphs.
Unique biological data types for data-intensive machine learning applications.
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