Balance the management of your capital investments by closely and more accurately tracking supply and demand activity. Monitor capacity levels based upon historical trends and forward looking business factors as inputs to advanced analytical models that can provide insights at your fingertips. Set inventory targets that more closely match projected demand to reduce imbalances.
Predictive Maintenance & QA
Applying KPI’s, machine learning, and AI models to your data can increase defect detection rates and reducing QA costs through multi-modal deep learning that can help business monitor visual defects and audio irregularities. Improve lifecycle cost analysis with the help of streaming data analysis (IoT, IIoT), real-time analytics/trending, and predictive models that can highlight potential maintenance needs or areas of potential failure. Sensor data availability and advances in edge computing can produce and assist in more proactive notifications and decisions.
Ingest ERP data from operational systems to provide integrated insights into Financials, Orders, Logistics, Warehouse Transfers, Inventory Tracking, Sales Tracking, and Channel Management.
Edge / Machine Data / RPA
Integration of your machine / sensor data for improvements in telemetry data management. Implementation of optimized and secure data techniques and capabilities on both edge devices, remote infrastructure, on-prem, and cloud compute.