This is quite challenging for health and life providers due to rising volumes of claims arising from chronic disease and aging populations. Processes are not scalable to handle more volume with respect to claims in health and life insurance. AI automation can help with this, but more tailoring is required compared with other types of insurance.

For instance, Guidewire was formed decades ago to sell the first standardized property and casualty insurance. Health insurance is much tougher. "You can't automate in a simplistic way, like you could for a broken car windshield," said Paris-based entrepreneur Tarik Dadi in an interview with TechCrunch.

His startup, Qantev, is attempting to solve that. He sells software to clients such as AXA and Generali that helps them process claims using AI models running similar checks that in-house medical staff does currently : "Is the care medically necessary? Is the price right? Is the bill fraudulent?" But it does so much faster. The company saves money, but more importantly, there is less churn.

Dadi saw that need while working as a senior data scientist at AXA, while now-CTO Hadrien de March, a doctorate and former quant, had the math chops to address it. The two of them joined forces at Entrepreneur First in late 2018. "EF's concept is 'pre-idea, pre-team,' but I cheated and brought the idea," Dadi said.

That sparked the seed round that Qantev raised €1.7 million led by Elaia in 2020 followed by the 10 million euros Series A led by Omnes and Raise Ventures last year. Today, these three firms are co-investors in the new 30 million euros Series B round of Qantev-an event that is surfacing earlier than Qantev had planned for, Dadi said.

"Our topics are pretty hot now, and we realized that YC, at the beginning of the year, included at least three of our topics in their wishlist," he says, referring to Y Combinator's Request for Startups and to what he calls the "LLM craze." "We started seeing lots of little startups sprouting up in the U.S. and just slapping an LLM on the problem.". [… ] we know it's a hard problem and that we are an asset. "

He's certain of one thing in the past five years, however: one big model is not enough; its software relies on a set of AI models trained on historical data coming from its clients, and accuracy is the goal. "You can't have hallucinations or anything like that. It's human health; you can't refuse care for someone's cancer.". That is why we are still a big AI shop. We have many PhD and ML experts in our team, because we have to create small AI models that are highly specialized in our topics," Dadi said.
Qantev is aware that it may yet be overtaken by new entrants, and the company's board acted with the latest round of funding in mind to attract all its AI and engineering talent in order to maintain its technological edge. Its stated goal is to double its headcount by year's end.

Qantev, which raised $20 million in a Series B round led by Blossom Capital, is also planning international expansion. It has stated its intentions to expand its Asia-focused Hong Kong office and make a strong push into North America.

While it faces competitors there, too- Alaffia Health and Anomaly among them- other Blossom portfolio companies have been making great inroads in the U.S. in recent years, and Qantev has its own advantage: Its customers are huge and global, so they generate organic expansion when a new subsidiary embraces their software.

But the downside is that the sales cycle is long and complicated. "But the upside is that they're big-ticket items," Dadi said. He liked Blossom's grasp of enterprise software as a category, and of Qantev's ambition to become an operating system for health insurance. "We like saying it is a platform, because it's going to be multiple products."

What those products will be is unknown, though underwriting stands out as a likely first fit. Qantev may remain claims-management-centric, but it's simple to envision how it can leverage the legitimacy and access to data it is building with its early customers to help them streamline other functions as well, such as it is doing currently around fraud detection. This, on a larger scale, would feed back into the trend that was already established of AI as a means to fight spiraling healthcare costs.