Tech
The back office problem that explains why specialists never call you back
A lot of the conversation around AI in healthcare focuses on diagnostics and drug discovery or on doctor-patient visits. But a less visible part of the system affects whether patients actually get seen at all, and it has less to do with the number of doctors in the world (too few) and more with the administrative work (too much) that happens between a primary care doctor writing a referral and a specialist’s office getting a patient on the schedule. That gap, it turns out, is huge, stubbornly manual, and increasingly attracting serious interest from venture capitalists.
Kaled Alhanafi, CEO and co-founder of Basata, grew up in Jordan and came to the U.S. to study computer science. He spent five years at Lyft, eventually overseeing operations teams covering most of the country, then went to Cruise, the self-driving car company, where he served as general manager for the Phoenix market. One of his co-founders, Chetan Patel, has a PhD in biomedical engineering with a focus in neuroscience and spent a decade at Medtronic building implantable cardiac devices. The two met in college and reconnected when their careers converged on the same problem.
For Patel, the issue became personal when his wife fainted on a flight with their young children. Even with his deep knowledge of cardiology and the specific devices that could help her, he says navigating the administrative process to get her appropriate care took far longer than it should have. “We have the best doctors, we have some of the best medicines, but the care gap is just so wide,” he said.
Alhanafi describes a parallel experience with his own father, who was referred to three cardiology groups after a serious carotid artery diagnosis. According to Alhanafi, only one called back within a couple of weeks. Another responded after the surgery was already done. The third still hasn’t called.
These aren’t unusual outcomes, as nearly anyone who has tried to see a specialist in recent years can attest. Specialty practices that receive referrals are frequently processing hundreds or thousands of documents — most arriving by fax — with small administrative teams. Practices lose patients not because they don’t want to see them, the company argues, but because they can’t get through the intake backlog.
Basata, founded two years ago in Phoenix, is trying to fix this. When a referral comes in — still typically by fax — Basata’s system reads and processes the document, extracts the relevant clinical information, and then an AI voice agent calls the patient directly to schedule the appointment.
Patients can also call the practice at any hour and reach an AI agent that can answer questions or handle common administrative needs like prescription renewals. Alhanafi says the company has recordings of patients audibly surprised by how quickly they’re contacted after a referral is sent. The goal, he says, is for a patient to have a scheduled appointment by the time they reach their car in the parking lot after seeing their primary care doctor.
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The company integrates with the electronic medical record systems that specific specialties actually use, which is why it says it has moved carefully — cardiology first, then urology — rather than trying to serve every corner of the market at once. The founders say they recently turned down a large deal in a specialty they haven’t yet mapped thoroughly enough to feel confident doing well.
The revenue model is usage-based: practices pay per document processed and per call handled, rather than per seat. The company says it has processed referrals for roughly 500,000 patients to date, with about 100,000 of those coming in the last month alone.
Basata says it has raised $24.5 million in total, including a new $21 million Series A round led by Lan Xuezhao of Basis Set Ventures, who began her career modeling the human brain as a PhD researcher before moving into corporate strategy at McKinsey and Dropbox and ultimately into investing. Cowboy Ventures, founded by Aileen Lee, also participated, as has Victoria Treyger, a former general partner at Felicis Ventures who more recently stood up her own venture firm, Sofeon (this is its first investment).
The space is getting crowded. Tennr, a New York-based startup founded in 2021, has raised over $160 million to date — including from Andreessen Horowitz, IVP, Lightspeed, and Google Ventures — and is now valued at $605 million. Tennr focuses heavily on document intelligence and has says it has built proprietary language models trained on tens of millions of medical documents. Assort Health, backed by Lightspeed, focuses on automating patient phone communication for specialty practices and last year raised at a $750 million valuation.
Lee said the founders’ years of experience are an asset in a space filling up with well-funded competitors. “There are a lot of [VCs] chasing around high school drop-outs and college dropouts, but when you’re selling to medical practices, trust is a really big deal,” she said. “These doctors want to look you in the eye and know that they can count on you.”
Basata’s founders meanwhile argue that their differentiation lies in combining both capabilities into a single end-to-end workflow tailored to specific specialties instead of building a tool that handles just one part of the process. That may be harder to sustain as better-funded competitors expand, but there’s clearly a market signal here.
Of course, like many AI companies automating work that humans currently do, Basata will eventually face a harder question about where the line is between augmenting workers and displacing them. For now, the founders say the administrative staff they work with aren’t worried about that; they’re more worried about drowning. Indeed, Alhanafi notes that the administrative staff at specialty practices have often been in their roles for decades and know the work intimately; they’re also buried in volume that no reasonable number of hires could fully absorb.
Whether AI merely expands what these workers can do or gradually makes many of their functions unnecessary is a question that applies well beyond healthcare. For now, Basata’s pitch is the former: that freeing administrators from the most repetitive parts of the job makes them better at the rest of it. Judging by one stat shared by Alhanafi — that 70% of the company’s new deals now come through word of mouth — it seems the people closest to the problem find that argument convincing.
Pictured above, left to right: Chetan Patel, who is co-founder and president of Basata; Kaled Alhanafi, the company’s CEO; and Vivin Paliath, the company’s third co-founder and CTO.
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Tech
Truecaller takes its scam intelligence to the open web as it looks beyond caller ID
After more than a decade building a caller ID business serving over 500 million users, Truecaller is now taking the scam intelligence it gathered along the way to the open web, with no app or sign-in required.
The Swedish company on Sunday launched Scam Checker, a new web and Android service that lets users paste in a suspicious phone number, link, or message to find out if it’s fraudulent. To work, the service surfaces related reports from Truecaller’s community, ScamFeed. However, more detailed information about a phone number, including the name associated with it, remains available only through Truecaller’s existing service, which requires a sign-in.
The free-to-access tool will initially be available in India and is set to expand to Latin America, the Middle East and Africa, and Southeast Asia, the company said.
In addition to serving as lead generation for its app, the community reports can give Truecaller a better view of the scams circulating at a given time. This could also help the company with its fraud and risk products sold to enterprises through Truecaller for Business, although Jhunjhunwala said Scam Checker itself is aimed at consumers.
To work, Truecaller’s Scam Checker checks the link the user submits, expanding shortened URLs and following redirects to the final destination. It then checks these against its proprietary risk database and other fraud signals. Users can also paste a suspicious message, allowing the service to pick out a phone number or link and surface related reports from the Truecaller community.

The launch comes as scams have grown well beyond phone calls to text messages, messaging apps, and web links. In a 2025 GSMA survey of Indian adults (PDF), 46% of those who reported being scammed said they were approached through messaging apps, while 37% via SMS and 32% through voice calls.
Truecaller estimates that people make about 14 million web searches a month to check suspicious links and phone numbers, based on its analysis of search volumes and traffic to existing verification services. That behavior helped shape Scam Checker, CEO Rishit Jhunjhunwala told TechCrunch.
“When you need it, you’re usually somewhere else. The link shows up on WhatsApp. Your mum gets a message about a traffic fine. A friend forwards you a screenshot and asks, ‘Is this real?’” Jhunjhunwala said. “What people do in that moment is search.”
Truecaller’s community is becoming a crucial piece of its scam-detection effort. The company told TechCrunch that about 20,000 scam reports are live on ScamFeed, its crowdsourced feed where users can post and discuss scams, in India, with around 1,300 new reports added each week. Between September 14 and 20, the company also said it evaluated 12.9 billion messages globally and flagged 20.3 million as fraudulent.
In the near future, Truecaller says it plans to broaden the types of scams Scam Checker can detect and add screenshot uploads for further analysis.
The company’s push beyond caller ID comes as its core business faces new pressures in India, its largest market with more than 350 million users. Telecom operators are rolling out the federal government-backed Calling Name Presentation service, while Apple and Google have added their own caller identification and spam-protection features. Last week, India’s telecom regulator also ordered caller-ID apps to share user-submitted spam reports with telecom operators, a move Truecaller criticized as a “one-way exchange.”
As a result, Truecaller’s focus is evolving beyond caller ID.
“Caller ID was the first problem we solved, and it’s still how most people find us,” he said. “But scams moved to a more multi-channel approach with links and messages, and increasingly to voice and video. Our protection has to follow the scammer.”
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Tech
Anthropic’s CEO is about to have dinner with President Trump
Anthropic CEO Dario Amodei seems to be everywhere this weekend: He was lampooned on the season premiere of Saturday Night Live, and tonight, he’s set to have dinner with President Donald Trump at the White House.
Axios first broke the news of Amodei’s dinner plans, which were subsequently confirmed by other publications.
This will be the first one-on-one meeting between the two men, who recently found themselves on opposite sides of the AI safety debate. Amodei released a plan to slow AI development (or at least proceed with more caution), while Trump has insisted, without evidence, that the AI backlash is a Democratic hoax; he also wants to rebrand the technology as “super intelligence.”
Even before the current back-and-forth, Amodei and Anthropic have to had a fraught relationship with Trump’s administration. Earlier this year, the Pentagon designated Anthropic a supply-chain risk in response to the company’s attempt to put guardrails around the use of its technology (Anthropic has been fighting the designation in court), although other administration officials have been friendlier.
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Tech
Can Muse overcome Meta’s trust issues?
Meta’s new AI agent Muse took the spotlight at the company’s annual Connect event, where CEO Mark Zuckerberg made it clear that Facebook’s parent company plans to push AI features everywhere.
On the latest episode of TechCrunch’s Equity podcast, Kirsten Korosec, Sean O’Kane, and I discussed Meta’s AI announcements seemed to steal the spotlight during a week of new model launches from OpenAI and Anthropic.
With other big AI companies focused on coding and enterprise tools, it was a little surprising to see Meta move in the opposite direction, with a consumer focus and a cute, Tamagotchi-style AI device that Meta insists is for adults only. But as Kirsten noted, this could be playing to Meta’s strengths.
Sean tried Muse for himself, and while he was pleased that the agent actually found him some unclaimed money, he described the feature as more “a party-trick type thing,” rather than something that will drive ongoing usage. Plus, there’s the question of whether users can trust Meta’s AI with sensitive information.
“Meta’s business is to sell you ads,” Sean said. “And yes, they’ll make the argument that the more they know about you, the more accurate and interesting the ads will be — wake me up when we get to that fever dream.”
Keep reading for a preview of our full conversation, edited for length and clarity.
Kirsten Korosec: So how do you put Muse, which is this new personal AI agent that’s just been released by Meta and [is] clearly a bet on consumer — how does that fit into what you just described, at least with other frontier AI model companies seeing opportunity and business within enterprise? Because Meta Connect, which is their big annual event, just happened, and they are all-in on Muse, that is very clear.
Anthony Ha: That was definitely very head spinning for me, because it certainly feels like what we’ve been talking about has been this shift towards enterprise — not exclusively, but certainly that’s where the money, the attention is going.
Maybe some of that is because of the relative position of these different companies — OpenAI and Anthropic are in the lead in a lot of ways, but also, they’re planning to go public either this year, or next year in the case of OpenAI. And so there’s this feeling of, “I think we’ve got to actually make money now.” Not to say that they’re not making money [already], but because the costs are so high and the valuations are so high, they have to make money on this scale that’s essentially unprecedented. And I think they’re seeing enterprise as the way to do that.
And I wonder if Meta, for a variety of reasons, sees a different opportunity. There’s a part of me that’s like, “Wait, did they not get the memo?” But I think more charitably, you could say, “Well, if that’s where OpenAI and Anthropic are going, then maybe there is more of an opportunity for Meta to make the more consumer-friendly [version and] continue advancing AI on the consumer side.”
Kirsten: I mean, we can complain about or criticize or critique Meta all day long, but they’re very good and have [an] established track record of embedding themselves in everyday people’s lives. I mean, there’s a reason why Facebook has so many users — Instagram, WhatsApp. And I’ve never really thought of them as an enterprise product anyway. So I think it’s smart for them to continue to push on the consumer piece.
Sean, you’ve already tried Muse, which has already been out for a couple weeks. And I’m wondering if you see what your impression is, and if you see it being successful in the bid to become part of every part of your life.
Sean O’Kane: I mean, not really. I understand why some people think that is going to be the case. I’m sure a lot of people understand this, but this is roughly Meta’s kind ground-up version of an on-your iPhone, or on your Android, app of OpenClaw, which we talked about a couple months ago, which Meta went out and basically bought and integrated those folks’ work. It was the first big explosion of like, “Holy smokes, these agents can do all this stuff for me while I’m out and about, and I can just text with it and let it control my whole computer.” There’s a lot of the same elements of that at play. And having it in your hand, on an app that works like a relatively good chatbot as the interface, it does seem pretty powerful.
One of the first things that I did with it was — because it makes a bunch of suggestions for you, as to things that it can do, and one of them was, “I’ll scan to see if you have any unclaimed funds,” this thing that I think no one ever really thinks about and often is going to completely miss, because there’s just not a lot of unclaimed property funds out there in your name. Surprise, surprise, there were some for me.
It helped me make some money on my first day, and that was pretty cool. I wouldn’t have done that if I hadn’t been prompted by this thing to do it. And there’s a check on its way to me in the mail. Fantastic. [But] that ends pretty quickly, right? That was a one-time shot, but it’s not a thing that’s repeatable. That’s more like a party trick-type thing.
Kirsten: I mean, you just killed your own argument. I don’t see how that wouldn’t become wildly popular.
Sean: The more sustainable version of that, and the thing that Meta’s talked up a lot over the last couple of days, is taking that idea and applying it to your real, true everyday financials, like giving it your information for your credit card, your Gmail account, all this other stuff, do things that we’ve seen other companies do, like Rocket Money or whatever, where it’ll go cancel subscriptions that you’re not using or identify double charges, things that frankly the credit card company should be doing already.
And at that point you just run into that trust wall with Meta. I think one of the reasons that I was willing to explore this and was curious to stick with it a little bit — even through to today — is that somewhat shockingly, when I downloaded it, I just assumed that it would like really instantly prompt me and like plug me right into Threads, Instagram, Facebook, which I don’t really use ever, and pull up that context immediately.
But it didn’t. And it was working with me like I was a stranger at first, which made me more willing to use it, because I didn’t feel like Meta had everything on me already. But you can see, as you start to use it, it really tries to grab you and pull those things into the system, so that it can learn all this stuff about you.
I don’t know that I will ever trust Meta the same way. I think it’s an interesting timing for me, having just upgraded my iPhone and getting onto the new iOS with the new Siri that actually works and can do some controls on your phone in a way that is surprising and helpful, that it’s never been able to do. [I’ve been] thinking about how much I’ve been using that over the last week and how much more how much more willing I would be to have the Siri version of Muse take that information, because I just trust Apple more with that really sensitive information and not only trust it with the information from a cybersecurity perspective, but from the fact that its business is not to sell me a bunch of crappy ads.
Meta’s business is to sell you ads. And yes, they’ll make the argument that the more they know about you, the more accurate and interesting the ads will be — wake me up when we get to that fever dream.
And beyond the one-time money lever that I got, which was great, I don’t feel like I’ve found anything else that’s really all that useful — other than the fact that it is, to Anthony’s point, really tailored at keeping it sort of consumer-y in your interactions with it, with which I do think helps it and is why people are talking about it so much.
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