why aren't all 23 resolved? a statement only gets an assessment when the public
record can support or contradict it. opinions and what-ifs never can, and 0 checkable
ones are still open, waiting for their date. predictions held up or didn't;
assertions are supported or contradicted. on every card:
▮▮▮▮▮ certainty ·
▮▮▮▮▮ debate potential. speakers are clickable
Assertion Not checkable as stated
Jain: Infinitus AI performs significantly better than human healthcare counterparts
“So like any other technology system, we're not perfect. We're significantly better than human counterparts.”
Prediction Not checkable as stated
Jain: Core AI will commoditize; value lies in workflow and proprietary data
“Building the core technology is going to be commoditized over time, but actually delivering the value by being part of the workflow is where there's a lot of challenges and being able to use proprietary data to tune it.”
Assertion Not checkable as stated
Jain: Calling healthcare payers twice yields different answers 25% of time
“So you call the same payer twice for the same patient, and you will get different answers 25% of the time.”
Insight
Jain: People demand perfection from AI instead of human-level baselines
“People want perfection out of technology rather than comparing it to the human counterpart.”
Assertion Partly supported
Jain: Administrative delays stop 50% of chronic patients from starting therapy
“Almost 50% of patients who get on therapy, or who are supposed to get on therapy, a script is written, never get on that therapy because of the complexities and delays in those systems, which leads to a lot of avoidable medical cost that ends up in the ecosyst…”
Assertion Not checkable as stated
Jain: Major health payers built dedicated call centers for Infinitus AI
“That led us to have a lot of partnerships with the largest payers in the country, largest PBMs in the countries, where some of them have dedicated call centers just for EVA.”
Assertion Not checkable as stated
Jain: Payers correct errors 70-80% of time when AI pushes back
“And so we built a knowledge graph based on all the calls that we do, to know what right looks like, so that now our AI agents, if they hear something that seems wrong, will push back and say, can you check that again? And we find 70 to 80% of time when we push…”
Assertion Not checkable as stated
Infinitus AI has completed over 5M calls and 100M audio hours
“So just to put this in scale, we've done over five million phone calls, over a hundred million hours of audio, of conversations between machines and humans.”
Assertion Not checkable as stated
Infinitus retrieves 30% to 40% of healthcare call data digitally
“We've probably gotten rid of a few single digit percentage of phone calls entirely, but in a pretty good percentage of calls 30 to 40% of data we can now get digitally instead of needing on the phone.”
Insight
Jain: AI systems should communicate via APIs, not spoken English
“My thesis has always been, why should you have two machines talk to each other in English? They should talk to each other in bits and bytes.”
Insight
Jain: Healthcare enterprises find updating IVRs easier than building external APIs
“The reality is for some large enterprises, it's easier to update their IVR systems than it is to create an API, go through info security, and expose an API to an external party because they've never done that.”
Opinion
Jain: Healthcare AI buyers care about patient outcomes, not LLM selection
“Our customers don't care what models we use. They want to make sure they can deliver a better, faster, and more proactive experience to their patient populations.”
Assertion Not checkable as stated
Jain: Silicon Valley talent is shifting from ads to healthcare tech
“And it turns out Silicon Valley Is getting an injection of people that have spent their careers working on ads and games that as they go through their careers go, I want to do something that matters to me.”
Prediction Not checkable as stated
Jain: Recruiting AI talent is getting easier as foundation tooling improves
“Getting the best talent is important. I think it's getting easier over time. I think it's because every major Company building in AI, the foundation models, is making it easier to fine tune, making it easier to bring your data, which becomes a moat, to be able…”
Disclosure
Jain: Infinitus supports nearly 45% of Fortune 50 companies
“I think we support something like 44 or 45% of the Fortune 50.”
Disclosure
Jain: Infinitus sells to healthcare labor budgets, not IT budgets
“We've never been part of the technology budget.”
Assertion Not checkable as stated
Jain: Healthcare RCM groups spend half their workday waiting on hold
“Many RCM groups spend more than half their day waiting on hold.”
Prediction Not checkable as stated
Jain: AI agents and EHR platforms will battle over integration layers
“And I think the agent companies are going to try to go down, the platform companies are going to try to go up, and it's going to be interesting to see how that plays out over the next couple of years.”
Assertion Not checkable as stated
Jain: Social determinants of health data is missing 80% of time
“Is everyone sees the potential of integrating social determinants of health data, but it's missing 80% of the time.”
Disclosure
Jain tested early voice AI by calling UnitedHealthcare as 'Bruce Willis'
“Before we incorporated Infinitus we built a demo that could call United Healthcare and say, hi, I'm calling to check benefits for patient Bruce Willis.”
Disclosure
Infinitus FastTrack AI navigates IVRs and waits on hold for employees
“So we have a co-pilot called FastTrack that goes through the IVR systems, waits on hold, and then drops in our customers, employees when the other person is ready to talk.”
Disclosure
Jain used his personal cell for hundreds of thousands of AI calls
“For the first three years of the company, that callback number was my cell phone. Right? And we were doing hundreds of thousands of calls. So I was getting 50 to 60 calls a day for various reasons.”
Assertion Not checkable as stated
Infinitus fine-tunes LLMs on hundreds of millions of labeled healthcare utterances
“The underlying infrastructure we have is focused on being able to rip and replace any model, the best one that's out there, and sometimes use multiple models from different vendors after fine tuning them with our hundreds of millions of utterances that are lab…”