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Robotic process automation (RPA) has found a strong foothold in the world of enterprise IT through its effective use of AI and other technology to help automate repetitive tasks, to free up people to focus on more complicated work. Today, a startup called Infinitus is coming out of stealth to apply this concept to the world of healthcare — specifically, to speed up the process of voice communication between entities in the fragmented U.S. healthcare industry.
Infinitus uses “voice RPA” to become the machine-generated voice that makes calls from, say, healthcare providers or pharmacies to insurance companies to go through a series of questions (directed at humans at the other end) that typically need to be answered before payments are authorized and other procedures can take place. Those conversations are then ingested into Infinitus’s platform to parse them for relevant information that is input into the right fields to trigger whatever actions need to happen as a result of the calls.
The startup is coming out of “stealth mode” today but it has been around for a couple of years already and has signed on a number of large healthcare companies as customers — for example, the wholesale drug giant AmerisourceBergen — and is in some cases contributing its technology to public health efforts around the current coronavirus pandemic, with one organization currently using it to automate a mass calling system across several states to get a better idea of vaccine availability to help connect the earliest doses with the most vulnerable groups that need them the fastest.
It made 75,000 calls on behalf of 12,000 providers in January alone.
Infinitus’ public launch is also coming with a funding kicker: it has picked up $21.4 million in Series A funding from a group of big-name investors to build the business.
The round is being co-led by Kleiner Perkins and Coatue, with Gradient Ventures (Google’s early stage AI fund), Quiet Capital, Firebolt Ventures and Tau Ventures also participating, along with individual investments from a selection of executives across the worlds of AI and big tech: Ian Goodfellow, Gokul Rajaram, Aparna Chennapragada and Qasar Younis.
Coatue is shaping up to be a huge investor in the opportunity in RPA. Earlier this week, it emerged that it co-led the latest investment in UiPath, one of the leaders in the space, having been a part of previous rounds as well.
“Coatue is proud to have led the Series A in Infinitus,” says Yanda Erlich, a general partner at Coatue. “We are big believers in the transformative power of RPA and Enterprise Automation. We believe Infinitus’ VoiceRPA solution enables healthcare organizations to automate previously costly and manual calls and faxes and empowers these organizations to see benefits from end-to-end process automation.”
The problem that Infinitus is addressing is the fact that healthcare, in particular in the privatized U.S. market, has a lot of time-consuming and often confusing red tape when it comes to getting things done. And a lot of the most immediate pain points of that process can be found in voice calls, which are the primary basis of critical communications between different entities in the ecosystem.
Voice calls are used to initiate most processes, whether it’s to obtain critical information, follow up on a form or previous communication, or pass on some data, or of course provide clearance for a payment.
There are 900 million calls of these kinds made in the U.S., with the average length of each call 35 minutes, and with the average healthcare professional who works in an administrative role to make those calls dedicating some 4.5 hours each day to being on the phone.
All of this ultimately adds to the exorbitant costs of healthcare services in the U.S. (and likely some of those inscrutable lines of fees that you might see on bills), not to mention delays in giving care. (And those volumes underscore just what a small piece Infinitus touches today.)
Founder and CEO Ankit Jain — a repeat entrepreneur and ex-Googler who held senior roles in engineering and was a founding partner at Gradient at the search giant — told TechCrunch in an interview that the idea for Infinitus first occured to him a couple of years ago, when he was still at Gradient.
“We were starting to see a lot of improvements in voice communications technology, turning text into speech and speech into text. I realised that it would soon be possible to automate phone calls where a machine could carry out a full conversation with someone.”
Indeed, around that time, Google itself had launched Duplex, a service built around the same principle, but aimed at consumers, for people to book appointments, restaurant tables and other services.
He determined that just being able to talk like a human and understand natural language wasn’t the only issue, and not even the main one, in enterprises applications like healthcare environments, which rely on specific jargon and particular scenarios that are probably less rather than more like actual human interactions.
“I thought, if someone wanted to build this for healthcare it would change it,” he said. And so he decided to do just that.
Jain said that Infinitus is using public cloud speech to text systems but the natural language processing and flows to triage and use the information gained from the conversations are built in house. The specialization of the content and interactions potentially is also one reason why Infinitus might not worry so soon about cannibalization from bigger RPA players, at least for now.
The fact that services like these — the new generation of robocalls, as it were — can sound “lifelike”, like actual humans, has been something that consumer versions have aspired to, although that hasn’t always worked out for the best. Duplex, for example, in its early days came under criticism for how it’s excellent quality might actually be deceptive, because it wasn’t clear to users they were speaking to a machine logging their responses in a data harnessing exercise. Jain notes that Infinitus is actually intentionally choosing voices that sound like bots to help make that clear to those taking the calls.
He said that this also “helps reduce the level of chatter” on the conversation and keep the person speaking focused on business.
On that front, it seems that while Infinitus works like other voice RPA services, connected up with live, human agents who can take over calls if they get tricky, that hasn’t really needed to be used.
“Today we don’t need to triage with humans because we see high enough success rates with our system,” he said.
You might wonder, why hasn’t the healthcare industry just moved past voice altogether? Surely there are ways of exchanging data between entities so that calls could become obsolete? Turns out that at least for now that isn’t something that will change quickly, Jain said.
Part of it is because the fragmentation in the market means it’s hard to implement new standards across the board, covering hundreds of insurance payers, healthcare providers, pharmaceutical groups, billing and collections organisations and more. And when it comes down to it, a phone call ends up being the easiest route for many admins who might have to typically deal with 100 different payment companies and other entities, each with a different logging mechanism. “It’s a lot of cognitive load, so it’s often easier to just pick up the phone,” Jain said.
Bringing in voiceRPA like Infinitus’s is part of that long haul to update the bigger system.
“By automating one side we are showing the other side that it can be done,” Jain said. “Right now, there are just too many players and getting them agree on one standard is a gargantuan task, so trying to winning one small piece after another is how it’s done. It should not be voice, but by the time standards bodies agree on something else, the world has moved on.”
As startups have stayed private longer and liquidity has become harder to secure for early employees and investors, more and more shareholders have looked for ways to unload their shares to others. All the way back in 2011, companies like SecondMarket were seeing nine-figures worth of shares being traded on their secondary share platforms.
That wave of liquidity startups ran into two problems: one was regulatory, and the other was a lack of company information about cap tables and that company’s current financial picture. Stock buyers were essentially flying blind while buying into companies, which some investors were more than willing to do, but that blindness limited the market demand for secondary shares significantly.
Carta is hoping that its base as the cap table management solution of choice for many startups will allow it to parlay that position into a new service it has called CartaX. We’ve heard rumblings about the service for more than a year now, but according to a new blog post by founder Henry Ward, it looks like the product is exiting beta and starting to operate in the real world with real money.
Yesterday, Carta sold just shy of $100 million of its shares across 1,484 market orders to 414 participants through its own CartaX product at a price of $6.9 billion. Ward says that is up from the $3.1 billion valuation of the company’s Series F round from last year.
As a comparison, secondary transactions typically involve secondary buyers who negotiate these deals manually one-on-one with individual sellers. What makes CartaX interesting is that it could allow for much faster and more frequent secondary sales at companies based on the same sort of computerized trading models that currently power the stock market.
Liquidity is a huge issue for startups, and while CartaX is just getting going, it fulfills a key need for many participants in the startup ecosystem, and it’s a key financial product to watch as it expands in 2021.
Meanwhile, revenues are looking good at Carta these days. According to an article earlier today by Zoë Bernard and Cory Weinberg at The Information, Carta has an ARR of $150 million. That’s a 46x revenue multiple if all the numbers are correct, which these days is good if not great for SaaS companies approaching the public markets.
Twitter is upping its data analytics game in the form of an expanded, multiyear partnership with Google Cloud.
The social media giant first began working with Google in 2018 to move Hadoop clusters to the Google Cloud platform as a part of its Partly Cloudy strategy.
With the expanded agreement, Twitter will move its offline analytics, data processing and machine learning workloads to Google’s Data Cloud.
I talked with Sudhir Hasbe, Google Cloud’s director of product management and data analytics, to better understand just what this means. He said the move will give Twitter the ability to analyze data faster as part of its goal to provide a better user experience.
You see, behind every tweet, like and retweet, there is a series of data points that helps Twitter understand things like just how people are using the service, and what type of content they might want to see.
Twitter’s data platform ingests trillions of events, processes hundreds of petabytes of data and runs tens of thousands of jobs on over a dozen clusters daily.
By expanding its partnership with Google, Twitter is essentially adopting the company’s Data Cloud, including BigQuery, Dataflow, BigTable and machine learning (ML) tools to make more sense of, and improve, how Twitter features are used.
Twitter declined request for comment but CTO Parag Agrawal said in a written statement that the company’s initial partnership was successful and led to enhanced productivity on the part of its engineering teams.
“Building on this relationship and Google’s technologies will allow us to learn more from our data, move faster and serve more relevant content to the people who use our service every day,” he said.
Google Cloud’s Hasbe believes that organizations like Twitter need a highly scalable analytics platform so they can derive value from all their data collecting. By expanding its partnership with Google, Twitter is able to add significantly more use cases out of its cloud platform.
“Our platform is serverless and we can help organizations, like Twitter, automatically scale up and down,” Hasbe told TechCrunch.
“Twitter can bring massive amounts of data, analyze and get insights without the burden of having to worry about infrastructure or capacity management or how many machines or servers they might need,” he added. “None of that is their problem.”
The shift will also make it easier for Twitter’s data scientists and other similar personnel to build machine learning models and do predictive analytics, according to Hasbe.
Other organizations that have recently turned to Google Cloud to help navigate the pandemic include Bed, Bath and Beyond, Wayfair, Etsy and The Home Depot.
On February 2, TC’s Frederic Lardinois reported that while Google Cloud is seeing accelerated revenue growth, its losses are also increasing. This week, Google disclosed operating income/loss for its Google Cloud business unit in its quarterly earnings. Google Cloud lost $5.6 billion in Google’s fiscal year 2020, which ended December 31. That’s on $13 billion of revenue.
Virtual health and wellness platforms have grown increasingly popular throughout the pandemic, but a new startup wants to focus that effort exclusively on senior citizens. Bold, a digital health and wellness service, plans to prevent chronic health problems in older adults through free and personalized exercise programs. Co-founded by Amanda Rees and her partner Hari Arul, Bold picked up $7 million this week in seed funding led by Julie Yoo of Silicon Valley-based Andreessen Horowitz.
Rees said in an interview that the idea for Bold came from time she spent caring for her grandmother, helping her through health challenges like falls. “I kept thinking about solutions we could build to keep someone healthier longer, rather than waiting for until they have a fall or something else goes off the rails to intervene,” she said. Rees started Bold to use what she’d learned from her own experience in dance and yoga to help her grandmother practice maintaining balance to prevent future falls. “My passion really was around ways to sort of widen the aperture, and make these solutions more accessible and built for older people.”
The member experience is pretty straightforward. Users fill out some brief fitness information on the web-based platform, outlining their goals and current baseline. From that information, Bold creates a personalized program that ranges from a short, seated Tai Chi class once a week, to cardio and strength classes meeting multiple times each week. “The idea is to really meet a member where they are, and then through our programming, help them along their journey of doing the types of exercises that are going to have the most immediate benefit for them,” said Rees.
Bold’s funding round comes at a time of concern around ballooning healthcare expenses for older populations, and a focus on how to reduce these costs for both current and future generations. While falls alone aren’t necessarily complex medical incidents, they have the potential to lead to fractures and other serious injuries. Bold’s preventative approach to falls is a more active solution than necklace or bracelet monitors that send a signal to emergency services when they detect a fall. And by offering virtual programs, they can help at-risk older populations engage in exercise while avoiding potential COVID-19 exposure at gyms.
Research shows that this works. Even simple, low-intensity exercise can improve balance and strength enough to reduce the incidence of falls, which is currently the leading cause of injury and injury death among older adults.
Fewer injuries would mean less need for medical care, which would lead to money saved for hospitals and health insurers alike. That’s why in addition to their seed funding, Bold has plans to start rolling out partnerships with Medicare Advantage organizations and risk-bearing providers, which will help make their exercise programs available to users for free.
The recent Databricks funding round, a $1 billion investment at a $28 billion valuation, was one of the year’s most notable private investments so far.
For Databricks signaled its IPO readiness by disclosing to TechCrunch last year that it had scaled its revenue run rate from $200 million to $350 million in a year, so the new capital looked like the capstone on its private fundraising before an eventual public debut.
The Exchange explores startups, markets and money. Read it every morning on Extra Crunch, or get The Exchange newsletter every Saturday.
But I did have a few questions, starting with the price of the round.
At a $28 billion valuation and ARR of $425 million, Databricks is valued at around 66x top line. That’s steep, if not the highest number we can dredge up on the public markets. Of course, for Databricks shareholders, seeing the value of their stock rise so quickly is hardly a bad thing. They are hardly going to complain about having more paper wealth.
But what about the investor perspective? Does the price really make sense? The Exchange caught up with Battery Ventures’ Dharmesh Thakker earlier this week to discuss a number of things, one of which was Databricks’ round and pricing. Thakker is named in the Databricks Series D funding announcement, which brought Battery into the company.
What was surprising about our conversation was not that Thakker was bullish on Databricks — a company that he and his firm have backed since its $140 million, 2017 round when the company was worth just under $1 billion. What surprised me was that he thinks its new $28 billion valuation might be a little low.
Intriguing, yeah? So this morning for both of us, I’ve pulled out quotes from our chat to help explain how Thakker views the market for Databricks, unicorns at scale more broadly through the lens of risk-adjusted investing, and the scale of the market some unicorns are playing in.
At the close, we’ll remind ourselves what Databricks CEO Ali Ghodsi told TechCrunch when we asked him the same question. Let’s go!
Databricks at $28 billion
Here’s how the valuation part of my chat with the Battery Ventures’ investor went down:
The Exchange: I want to talk about Databricks, because I spoke to [CEO] Ali [Ghodsi] yesterday about this round, and hot damn, it’s a lot of money at a valuation that is roughly 64x ARR, give or take. I don’t understand the price, and I know it’s a boring thing to talk about. [It’s a] great company, I get their market, I’ve talked to them a bunch, I know their revenue numbers. [But] I don’t understand the price, and I was hoping you could tell me why I’m being too conservative.
Dharmesh Thakker: I, for what it’s worth, think [the price] fair. If anything, I think it is on the lower end — he could have done better, frankly. But I think it comes down to three major things, right?
One is the addressable market. Just think about the addressable market of data. If there’s a trillion dollars spent in software or technology, I think you and I would be both hard pressed to say, almost all of that [isn’t] influenced by some data-oriented decisioning. Whether it’s digital transformation, whether it’s analytics, data is everywhere. So the TAM is massive … I think you and I both agree on that, whether it is $20 billion or $80 billion — it’s massive.
Source: https://techcrunch.com/2021/02/04/why-one-databricks-investor-thinks-the-company-may-be-undervalued/
