The R1 platform leverages an array of advanced AI and machine learning methods, including in-memory neural networks, qualitative combinatorial maps, reinforcement learning and more to implement proprietary and unique data processes that enable the most accurate music data matching, conflict resolution, dynamic data merging and analytics.
Thanks to RYLTI R1’s unique data processing algorithms and underlying event-based architecture, machine learning and parallel matching of music catalogs, sales reports and royalty statements can be conducted with a fraction of the compute resources and in near real-time. The low compute requirement of the software enables RYLTI to perform machine learning and matching at a scale in which every data point is collected and used without down-sampling, providing smarter, comprehensive and more accurate music data matching results.
R1 Core consists of the frontend user interface and backend microservices for platform administration, user and data lake security, data modeling and mapping, workflow design, job processing and exception handling.
R1 Hub is the backend real-time and batch event bus, which enables AI and machine learning-based music data matching pipelines capable of handling hundreds of data sources concurrently. Examples include society catalogs (e.g. MLC), DSP sales reports from domestic and international music streaming providers, royalty payment statements from societies, and other data providers.
R1 Application Modules range from platform enhancement subsystems like R1 Analytics (Coming in Q4 of 2021) to pre-built integration adapters for popular streaming providers and fixed-length file format processing for society integration. RYLTI will also develop custom application modules via RYLTI Consulting or RYLTI partner-developed modules beginning in 2022.