ElectrifAi built a machine learning model to categorize and classify spend by vendor and identify small minority businesses. As a result, the city reduced its costs, increased supplier visibility, and was to redirect spend to minority-owned firms fulfilling diversity, equity, and inclusion pledges..
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Recovering $14 Million in Missed Medical Billing Charges
A small hospital system was losing money and didn’t know where it was going. It also experienced high costs, which meant the business lost millions of dollars annually. ElectrifAi leveraged machine learning to create a model that gave the client insight into potential missed charges. It also created user-friendly Ai dashboards to pinpoint billing issues. As a result, the hospital system spotted $14 million in confirmed missed charges, which both injected cash into the business and remedied its profitability challenges.
Reducing Procurement Spend
A card payment service needed to better understand its expenses, so it brought in ElectrifAi to leverage prebuilt spend analytics solutions. Its internal procurement team needed a tool for ongoing data maintenance so the business could improve its procurement abilities while reducing costs.
ElectrifAi consolidated and classified spend data so the client could manage its data internally. After classifying three years of historical business data, ElectrifAi successfully reduced procurement costs for the client. It also created a fully operational spend data set that the client’s team could manage internally.
Reducing Supply Chain and Customer Risks
A leading manufacturer in Asia wanted to better manage its cash flow and minimize supply chain risks. Its customers were chronically overstocking and understocking, which meant the manufacturer had significant problems with cash flow, delayed customer payments, and defaults.
The manufacturer tapped the ElectrifAi team to improve its cash flow stability. ElectrifAi used predictive metrics to identify at-risk clients in real time. As a result, the client reduced supply chain and credit risks across its 20,000 customers.
Defining Customer Journeys With Test-and-Learn Capabilities
ElectrifAi partnered with one of the top three wireless providers in the U.S. to improve its customer experience. The brand had plenty of customer data, but it was too siloed. As a result, its customer retention and product cross-sell/upsell programs weren’t working as well as planned.
