Data loading and ingestion into Mtell Reservoir occurs across multiple sites using third- party tools. Data are ingested in real-time streams, batch uploads, or import of comma-separated (CSV) files. Reservoir intrinsically accepts data from the Mtell CloudSync service attached to distributed Previse systems. Its elegant and sophisticated bi-directional architecture ensures CloudSync performs stream-based processing across challenging and bandwidth limited network connections such as satellite links. Transmitted streams include sensor data values, alerts, events, and maintenance activities. Automatic, lossless data compression means more efficient data transfers, and dynamic throttling keeps transfer within configured bandwidth limits. Signal prioritization assures the most pertinent data are received first, and the system will recover older data as bandwidth becomes available. CloudSync also delivers machine learning signatures from Mtell Summit into monitoring Agents at remote sites.