CURIO | Platform

The CURIO™ Platform

The CURIO platform was designed and built by an expert team of product developers with decades of “big data” software development experience to make easy work of any agrigenomics task in a way that is fast, efficient, and user-friendly.

The power behind CURIO comes from its unique and proprietary cloud-based architecture that provides fast and reliable results for a broad spectrum of applications and computational demands. From deep research to high-throughput operations, CURIO is the all-in-one solution for your agrigenomics needs.

Massively scalable enterprise engine for high-volume genomics operations
CURIO provides rapid and scalable solutions that streamline the sequencing process for large populations. This efficiency is crucial for breeders who need to analyze extensive genomic data to make timely, data-driven decisions on breeding programs, ultimately enhancing desired traits.

CURIO enables breeders to handle vast datasets with ease and reliability. Additionally, the ability to share and collaborate on data in real-time fosters a more integrated approach to breeding, ensuring that findings can be swiftly translated into practical applications. This operational efficiency not only accelerates the breeding cycle but also enhances the commercial viability of breeding programs by providing actionable insights at unprecedented speeds.

Typical use cases: LPS + Imputation,
I just did in 1 hour what would have taken our team 3 months.
John Baison, Ph.D., Cereal Geneticist, RAGT Seeds
NGS - Deep Research
Robust, end-user research software for deep data analysis and visualization
CURIO is a proven platform for agrigenomics research focused on identifying rare SNPs and facilitating collaborative research environments. The platform's ultra-parallelized cloud-based bioinformatics enables researchers to conduct deep genomic analyses, identifying elusive SNPs with precision and speed.

CURIO’s intuitive interface and comprehensive toolset support collaborative efforts among multidisciplinary teams. Researchers can share real-time data, adjust parameters dynamically, and visualize results together, enhancing the efficiency and effectiveness of collaborative projects. This seamless integration of tools and collaborative features accelerates the discovery process and enables researchers to tackle complex agrigenomic challenges more effectively.

Typical use cases:

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