ElectrifAi, a machine learning (ML) and artificial intelligence (AI) solutions organization, has collaborated with Vizzia Technologies, a provider of real-time location systems (RTLS) for healthcare organizations, to deliver machine learning-powered inventory optimization for advanced asset management predictive analytics.

This collaboration aims to reduce costs, streamline processes, and enhance patient care at leading hospitals by analyzing critical medical equipment utilization levels, according to the companies.

An extensive pilot was conducted at one of Vizzia’s customer sites. The pilot yielded substantial operational improvements across several inventory KPIs to include: up to a 52% improvement in key out-of-stock metrics; and reducing overstock rates by up to 20%.

“We are very pleased to partner with Vizzia and contribute to their mission of transforming healthcare asset management,” says Edward Scott, ElectrifAi’s CEO. “Our ML-powered Inventory Optimization solution provides an advanced approach to equipment utilization, which helps hospitals to reduce costs and improve patient care.”

The ElectrifAi Inventory Optimization solution leverages IoT input data, time-series analysis, and category-specific trend analysis to generate accurate PAR level predictions, preventing overstocking or understocking.

“Our collaboration with ElectrifAi has significantly enhanced our ability to deliver cutting-edge inventory management efficiencies to our clients,” says Andrew Halasz, CEO of Vizzia Technologies. “We greatly appreciate the deep AI & ML insights that the ElectrifAi team of data scientists provided to our InVIEW platform.”