![Artificial Intelligence Startup, Rehinged, Launches Carenet AI](http://media.assettype.com/cdo%2Fimport%2Fcdomagazine.tech%2Fcontent%2Ftncms%2Fassets%2Fv3%2Feditorial%2Ff%2F6d%2Ff6db5e7c-807a-11ec-b7ca-bb1e4b63258e%2F61f4559356e32.image.jpg?w=480&auto=format%2Ccompress&fit=max)
(US and Canada) Rehinged, Inc., an AI startup that transforms external market data into actionable intelligence, today announced the launch of Carenet AI, their market intelligence platform specifically built for the healthcare industry.
"The healthcare market is the perfect entry point for the commercialization of the Rehinged AI platform," said Jim Sagar, founder and CEO of Rehinged. "It's a 4.1 trillion-dollar market and 19.7% of the U.S. GDP. There's a tremendous volume of data, a tremendous market need and tremendous value when providers are matched to the facilities with the greatest need."
Carenet AI is a new brand that speaks directly to the needs of commercial teams at companies selling into United States healthcare facilities. The platform is a complex cloud-based series of applications that turn real-time data into actionable intelligence for end-users.
"While there are some data options available in the healthcare space, such as Definitive Healthcare, the challenge for commercial teams is twofold: good, reliable data is expensive, and it's very difficult to make that data actionable for a commercial team," said Robert Crousore, Rehinged investor and its healthcare commercialization strategist. "Carenet AI solves these problems. Real-time, actionable data is the holy grail for teams forced to sell from their home office, instead of meeting directly with doctors and care providers."
Commercial healthcare and med tech teams selling into nursing homes, doctor's offices, long-term care facilities, hospitals and other clinical care facilities can get a dynamic feed of their ideal customer targets based on digital signals emitted daily, weekly, monthly and quarterly.
For each customer, Carenet AI identifies the relevant combination of data containing their ideal customer signals then combines and scores it to automate prospecting. This eliminates the need to invest in data science and data engineering infrastructure to make their commercial data actionable.