These Former Googlers Raised $30 Million To Automate Phone Calls With Health Insurers

Eva Lightyear has made around 250,000 phone calls to some of the biggest health insurers in the country over the past year and a half. She’s helped 35,000 healthcare providers figure out how their patients’ insurance works — the copay, coinsurance, deductible and prior authorization requirements. And like her namesake Buzz, the space ranger of Pixar’s Toy Story fame, Eva isn’t a human. She’s a robot. 

Eva L., as she’s known to most of the people she talks to on the phone, is the creation of Infinitus Systems, a San Francisco, California-based startup that is automating one of the most tedious and time consuming administrative processes for many doctors’ offices, hospitals and pharmacies: verifying patient health insurance benefits. It’s a back office function that usually involves at least two humans, lengthy wait times and answering the same questions over and over again. “She makes the phone call and talks to the human on the other side, but in doing so we’ve standardized how these phone calls happen,” says CEO Ankit Jain, 36, who cofounded Infinitus with CTO Shyam Rajagopalan, 35, in 2019. 

By creating standard data elements, using APIs to get more digital information and shortening the time of these calls, Infinitus is laying the groundwork for a much bigger healthcare administration transformation — saying goodbye to phone calls and fax machines. (Yes, fax machines, which remain ubiquitous in healthcare). “If we played this forward a few years, it’s natural to have machines that are either making the phone calls or receiving the phone calls,” says Jain. “But if you ever have machines on both ends, they really shouldn’t talk in English. And that is the future that we’re building towards.”

It’s a vision that top venture capitalists are willing to support. On Wednesday, Infinitus announced a $30 million Series B led by GV (formerly Google Ventures) with participation from existing investors Kleiner Perkins and Coatue Management. The company is also backed by a roster of individual investors, including Aashima Gupta, the director of global healthcare strategy at Google Cloud, Ian Goodfellow, the director of machine learning at Apple and Nat Turner and Zach Weinberg, the cofounders of Flatiron Health. The latest funding round values Infinitus at $275 million, according to a person familiar with the deal. The company has raised $51.4 million to date. 

Think of Alexa, Siri and the Google Assistant as the first generation technology. Now advances in voice recognition and natural language processing have made it possible for a robot not just to answer simple questions but to hold a conversation. And unlike the clunky, consumer-facing interactive voice response systems used by cable, utility and credit card providers that never seem to work, Eva is highly specialized for a business-to-business interaction. “These calls are so routine,” says Jain. “We’ve mapped out 98.99% of the pathways that happen in these conversations.”

These calls may be routine, but they are also major pain points in the broader healthcare system and stand in the way of patient care, as things like MRIs and cancer infusions get caught up in red tape. “There’s a lot of faxes and other older school technologies that go back and forth,” says Krishna Yeshwant, a managing partner at GV, who is joining the Infinitus board. “The whole system is constantly trying to communicate with itself and coordinate internally all in a relatively inefficient fashion.” But that’s also how Infinitus was able to get a strong toehold with customers: by focusing on automating a small piece of the $800 billion healthcare administrative headache rather than attempting a massive overhaul. It’s rare, especially in healthcare investing where it can take years for a product to get to market, to find a near instantaneous market fit, says Yeshwant. But talking to Infinitus customers, he sees the product “helping them right now.” 

Jain and Rajagopalan first met during middle school in the San Jose area and went on to be college roommates at UC Berkeley. A few years after graduating, they both ended up at Google, where Rajagopalan was on the security and compliance team working on Google’s login system and Jain was working on search and discovery for the online store Google Play. In 2013, the duo left to launch Quettra, a GV-backed mobile analytics company that was acquired by Similar Web a few years later. Following the acquisition, Jain went back to Google as the director of engineering and a founding partner of Google’s AI-focused fund Gradient Ventures, while Rajagopalan joined Snap. “Building an impactful, long-lasting business was something that we both had a deep passion for,” says Jain. “And we were looking for the right business and technology idea to go after.” 

In 2019, they decided to combine their engineering and AI skills to tackle automation in healthcare. One of their first big customers (secured via a cold pitch from Jain on LinkedIn) was the wholesale drug distributor AmerisourceBergen. Lash Group, which sits in AmerisourceBergen’s patient support services division, works to get patients access to expensive specialty drugs that treat cancer, central nervous system and retinal diseases that often require infusions. “Verification really becomes the first step in getting the information to the provider to allow them to communicate to the patient — or directly to the patient — about what this journey is going to cost,”  says Jeff Buck, the vice president of strategy and analytics at Lash Group.

For the government-sponsored health programs Medicare or Medicaid, the Lash Group often relies on a homegrown AI-based system that can process verifications in 30 seconds. But it becomes a lot trickier with commercial insurance plans that have widely varying coverage, which is where the company has started to use Infinitus for a growing number of verifications. By removing the human staff from having to spend hours on hold with insurers each day, they can focus on more complex patient-facing problems. Eva can get through calls around 30% quicker and the quality is around 10% higher than humans, says Buck, since there are fewer miscommunications or typos. “We’re ultimately trying to use the technology to reduce the time to therapy, get the services done as quickly as possible at the highest quality, and repurpose our staff to more of the experience components of the work,” he says.

Now that Eva has mastered benefits verification, Jain hopes to add different types of phone calls, such as claims processing, denials and patient reminder calls. The company also plans to expand to more customers, including ambulatory surgery centers and revenue cycle management companies. Because, at the end of the day, Infinitus customers don’t want to stop at just phone calls. “In this next part of our journey, we want to start delivering on that promise of end-to-end process automation,” says Jain. Looking towards the future, he once again references Toy Story’s Lightyear: “To Infinitus and beyond!”