SaaS-maker Birdie has closed an $11.5 million Series A round of funding led by Index Ventures. Existing investor Kamet Ventures also participated.
The UK-based caretech startup has raised a total of $22.9M since being founded back in 2017 (a 2018 raise that was called a Series A at the time is now being classed as a seed expansion). It’s focused on building tools for social care providers to drive efficiencies in a chronically under resourced sector.
Birdie isn’t a care provider itself (so it’s not a direct competitor to a startup like Lifted); rather it aims to support care providers with a suite of digital tools intended to reduce admin costs and makes it easier to manage the care being provided to individuals — doing away with the need for paper-based records, and enabling real-time visibility such as via carer check-ins and medication-related notifications.
The wider mission is for the platform to support care providers to offer more co-ordinated, personalized and — the hope is — preventative care so that older adults can be supported to live for longer in their own homes.
“Technology can completely transform the way we look after the elderly and help them to age at home much longer, healthier and happier,” says CEO and co-founder Max Parmentier, explaining the founding premise. “We position ourselves as a solution to uniquely offer a full support for the elderly to age at home… So we started off with the people closest to the elderly and caring for the elderly which are the care providers. And when we look at how these providers are operating they are extraordinary committed, and very much involved in their work, but the care delivered is very uncoordinated, reactive and sometimes very generic.
“We felt that we could go way beyond — in terms of technology — becoming the operating system to be much more efficient in the way they deliver care but also to significantly increase the quality of the care delivered.”
What’s the draw for VCs to invest in such an under-resourced market? “There’s macro trends which are unavoidable. I agree with you that it’s vastly underfunded but it’s just unsustainable,” he argues. “There is clearly an argument to say that whether VCs or investors are interested in this industry or not it’s going to get bigger. And one way or another we’ll have to find some funding mechanism to pay for it.”
“Today already we hear horrible stories about older people not being taken care of properly. I think what got particular Index excited is really the opportunity to [tell a positive story],” he goes on. “I’m quite an optimistic person. I do believe that actually you could very much craft a much happier path in terms of ageing which is actually more affordable — because it doesn’t cost as much because you really lower the healthcare costs if you really tailor these packages better and tailor the care much better. And you can also use technology to make it more personalized, more preventative.”
By simplifying and streamlining data capture around elderly care via a digital platform, information about the care being delivered can be structured in a way that helps reduce errors (such as from handwritten notes leading to administering the wrong medication) and allows for problems to be spotted early when an intervention may be highly beneficial, is the contention.
Parmentier gives the example of early signs of a urinary tract infection which, if picked up on — by spotting telltale signs in the data — can be treated simply at home with antibiotics. But if not an elderly person may end up in hospital, with all the associated risks of a far worse outcome.
Birdie can also supply connected hardware like motion sensors to its care provider customers so that its platform can monitor frail elderly adults who may be at risk of falling. Although Parmentier emphasizes that such hardware is an optional component of the platform — and is only installed with the full knowledge and consent of the care recipient.
The business is focused on “serving the interests and the rights of these older adults and no one else”, he says, confirming that care recipients’ data is not shared with any third parties unless it’s directly related to the delivery of their care.
Having a digital platform-level view into an individual’s care obviously offers increased visibility vs paper-based records. It also means real-time data can be shared — such as with close family members who may want the reassurance of knowing when their loved one has received a visit or taken their medication, and so on. (Again, though, only with the proper consents.)
“There is a positive narrative which is that ageing is actually great,” Parmentier suggests. “If you’re in good health this part of your life is probably one of the most exciting. And this is really the spin we should give in terms of story but also we should empower these older adults with the right support to take that happy path.”
To date, Birdie has partnered with almost 500 providers across the U.K. — and currently its platform is being used to support the care of more than 20,000 older people every week.
Growth has been 8x over the past 12 months, per Parmentier, as the coronavirus pandemic has accelerated demand for in-home elderly care. The new funding will go on accelerating growth in the U.K., though he also says it has its eye on other geographies and sees potential to expand internationally.
“Phase one [of the business] is how can we empower these care providers to be better at what they do?” he says. “Because I really believe that there’s am army of care givers who are so committed and if we can help them be better at what they do that’s beautiful.”
Having structured data on elderly care provides a foundation for conducting research that could further the ‘preventative’ care component of the mission — and Birdie is taking some tentative steps in that direction via some project partnerships.
Such as one into polypharmacy (i.e. concurrent use of medications which can have negative clinical consequences) with U.K.-based AI company Faculty.
“There’s very little known as to what impact medication has on older adults health. If you think about it we just have pharma companies doing trials and then flagging secondary symptoms up when they arise and then doctors prescribe that. The reality is for elderly people — because usually they combine different medications — the symptoms and the damage to health can be greater,” he explains.
“What we’ve done with Faculty is to look at what is the medication treatment of an older adult and what is the clinical observations from carers following these medication treatments. So do we see that typically there’s less appetite to eat or drink, or complaints about pains and so on. And do we see correlations with the actual medication treatment prescribed?”
The polypharmacy research is at an early stage but he says the hope is they will be able to build an AI model that can generate warnings for a prescribing clinician if a particular medication regime has been linked to outcomes that may damage health or otherwise hamper healthy caring for an individual.
On the research side, Birdie’s website notes that it’s using “anonymized” data in these exploratory efforts — which is a claim that merits scrutiny given that medical data is both very sensitive and notoriously difficult to robustly (irreversibly) anonymize.
Asked about this, Parmentier says that for the moment its research efforts entail correlating data on different older adults from different care providers, and that the data being pooled is limited to specifically relevant info (i.e. depending on the research project) — removing “all the un-needed data”, as he puts it.
He says it is not, for example, currently combining any of the data it holds with National Health Service (NHS) patient data — which he acknowledges could pose a major risk of re-identification. But he also says Birdie does want to go there because it believes that combining more data-sets could help it further preventative care research.
“The risk is when you pool your data with any third party data-set such as the NHS for instance. That is really risky… because there’s always a way to tie it back. So we’ve been keeping away from that for the moment,” he tells TechCrunch.
“I think it can really improve our preventative models but we need to do that only under very strict conditions that the anonymization is bullet-proof,” he adds. “We haven’t done that yet and we’re exploring ways to do it. But we’re going to very cautious about it. So for the moment there’s no risk really because we’re not mixing data-sets of the same patient. But if we were to integrate with third parties’ systems the risk will rise — and we’ll need to address it very clearly.”
Parmentier also offers a glimpse of an ambitious potential second phase of the business — where Birdie believes it will be able to coach older adults themselves (and/or their family members who are acting as care givers), i.e. enabled by its platform-level view of best practice (and by being able to fold in data-fuelled research into preventative care AI models).
To get there will require not, just a lot of data, but a sectoral shift toward a model of care delivery focused on “value-based healthcare”; where the provider is billed not for hours of care given but on health/quality of life outcomes. So the transformative vision of highly scalable, data-enabled elderly home care is certainly not going to arrive overnight.
In the meanwhile Birdie’s business remains firmly in phase one: Building support tools to drive efficiency and quality for an under-resourced sector.
“We see the same problem everywhere,” adds Parmentier. “Today already we don’t look after our elderly properly… Today they cost us about 60% of our healthcare costs. Tomorrow is going to be much worse. We need to channel more investment into this industry — in terms of new ways of operating, technology, and really innovation is key to move towards better models where it’s more preventative, more personalized, more outcome based — because that’s the solution. It’s going to lower the cost base, it’s going to improve the health outcomes.”
Commenting in a statement, Stephane Kurgan, venture partner at Index Ventures, added: “Our ageing society and increasing healthcare costs require us to rethink the way we care for frailer populations like the elderly. Technology gives us the tools, as the care sector has remained widely paper-based and is ripe for disruption.
“By investing in caretech with Birdie, we are investing in solving the daily challenges of the care community. We firmly believe in Birdie’s vision to make care more personalised and more preventative so that older people can age at home longer, healthier and happier. We’ve been impressed by Birdie’s traction and the calibre of its team, and are very excited to embark on this journey with them.”
Usage of AI for Customer Behavior Analysis
The world is getting revolutionized with the impact of technologies like Artificial Intelligence and machine learning. These digital technologies have impacted various sectors and became valuable to humankind.
Artificial intelligence is the technology that has created a revolution in the business sector by offering advanced solutions and tactics for the effective growth of the business. Business people are keen on applying such digital solutions where they can take advantage of AI. They are getting digitally equipped by having an online platform through which they can run a business online as well as take advantage of AI and other such technologies.
“The fascination of AI has been disrupting the business sector like never before and rightly so because of the wings it offers to them to fly.”
In recent times, from small businesses to large scale, everyone is introducing digitization to their business to go on the digital floors. The online business concept has been a crucial turnaround in the business sector and elevated the business scope. Whether it is small grocers who build grocery apps to serve their audiences online or the supermarkets that run business digitally and advancing their consumer service, all of them are taking healthy advantage of digital solutions.
The adoption of digital solutions opens up the doors of innovation for business people to grow their business with concepts like AI. Artificial intelligence is the latest trend which business people are focusing on, and the variations it offers are impeccable.
One of the outstanding uses of AI in the business world is customer service. It can be a very valuable integration because it is the concept that can be used for key analysis on customer behaviour and offering an outstanding experience to consumers.
AI In Customer Behaviour Analysis
If you want to succeed in the business world, you need to acknowledge your customers and target audiences well enough. The more you know about them, the more you have a chance to succeed, and that is because you will be able to offer better service to them as you already have insights about them.
“The integration of AI gives the liberty of customer behaviour analysis to the business model, which can be very helpful for the growth of the business. “
Businesspeople used to do customer behaviour analysis before, but previously due to lack of technologies, it was way more time-consuming. With concepts like Artificial intelligence, things have become more accessible. It is the concept that helps in analyzing the customer behaviour deeply so that you can take proper actions to offer amazing services to customers and eventually reduce the churn rate.
Aspects Of Customer Behaviour Analysis With AI
Customer behaviour analysis can be a better sight for achieving business growth, and to comfortably execute it AI is there for you. Businesses need to deal with customer expectations, preferences, satisfaction, wishes, etc., and if they succeed in this, the customers will be happy. Thus, intelligent analysis is required to clear all the aspects in offering the best service.
Understanding Purchasing Habits
Artificial intelligence will allow business people to know and understand the purchasing habits of potential or current customers. AI records all the points of interaction with customers for deep analysis and extracting the best meaningful outcome from it. Artificial intelligence analyses the customer’s purchase habits by having records of data that has been collected.
Knowing Customer Expectations
Fulfilling customer expectations is very important in the business world. If you understand what customers are expecting in terms of product quality, quantity, tastes, use, prices, etc., and you are successfully delivering it to them. In that case, that is the best thing happening to your business. AI-powered businesses have the advantage of understanding customer expectations through various customer behaviour analyses.
Forecasting Customer Needs
Forecasting customer needs can be very advantageous, and artificial intelligence is here for you to analyze customers’ future needs. Different customers have their individual requirements, and with AI, personalized approaches can be provided. The analysis of customer behaviour will allow them to forecast the needs of customers, and it will help in recommending the products and services in advance, which will be very effective in increasing sales.
How AI Does Customer Behaviour Analysis?
Artificial intelligence is the technology that records information about customers’ sentiments when they surf the internet world. AI collects the requisite information and extracts meaningful insight from it, which helps understand customer behaviour through analysis. The insights like buying preferences and frequencies are revealed with the help of Artificial intelligence.
Reduction In Churn Rate With AI
The customer behaviour analysis will elevate the customer experiences as business people will take some actions depending on the output of the analysis. The churn rate is something that business people need to reduce to grow their business. Artificial intelligence will help business people to improve their churn rate because of customer behaviour analysis.
- Empower business as AI drives better customer service
- Greater customer experience by understanding customer behaviour.
- Hence, betterment in customer service will reduce the churn rate.
Due to the analysis, the businesses will be able to offer better experiences to customers by improving customer service. The betterment in the customer service will have a good impact on the business model, and customers are likely to enjoy it, which will increase customer retention. Thus, businesses will not lose customers, and their churn rate will not be reduced.
Cultural Shift In Business World Must Occur
The business sector is still in the initial stage of integrating such advanced technologies as Artificial intelligence. According to Forbes, only 23% of current business respondents use AI for running their business. Business people need to understand the importance of AI and other such technologies. That is how the cultural shift in the business sector will happen, which will have more room for advanced technologies.
The main reason behind business people not actively supporting integrating the technologies is the realization of their importance. Another important reason is that they believe in hype that these technological solutions are very complex. If the efforts are put in integrating such, it offers a great outcome for them. Thus, the realization of the importance will lead the path of the cultural shift in the business sector.
“The technological shift in the business sector will open new doors of innovation and discover the new path of success”
Artificial intelligence can create a crucial turnaround in the entire sector because of its verticals. Customer behavior analysis being the most advantageous factor of integrating AI in the retail sector. Thus, the scope of AI in business is wide and fruitful.
The use of AI in customer behaviour analysis will greatly impact the ventures and give it better scope for succeeding. The analytical solutions it offers are outstanding. There are major benefits to the business if they are able to understand and predict their customers’ behaviour regarding their products and services.
The current industry giants are already using AI and have great benefits in getting popularity. The rise in overall business standards is the excellent advantage of integrating technology solutions. Thus, with time and room, AI will continue to disrupt the commercial sector with its wings.
— Brijesh is the tech activist, blogger, and internet marketing officer of Elluminati Inc
Nvidia’s Canvas AI painting tool instantly turns blobs into realistic landscapes
AI has been filling in the gaps for illustrators and photographers for years now — literally, it intelligently fills gaps with visual content. But the latest tools are aimed at letting an AI give artists a hand from the earliest, blank-canvas stages of a piece. Nvidia’s new Canvas tool lets the creator rough in a landscape like paint-by-numbers blobs, then fills it in with convincingly photorealistic (if not quite gallery-ready) content.
Each distinct color represents a different type of feature: mountains, water, grass, ruins, etc. When colors are blobbed onto the canvas, the crude sketch is passed to a generative adversarial network. GANs essentially pass content back and forth between a creator AI that tries to make (in this case) a realistic image and a detector AI that evaluates how realistic that image is. These work together to make what they think is a fairly realistic depiction of what’s been suggested.
It’s pretty much a more user-friendly version of the prototype GauGAN (get it?) shown at CVPR in 2019. This one is much smoother around the edges, produces better imagery, and can run on any Windows computer with a decent Nvidia graphics card.
This method has been used to create very realistic faces, animals and landscapes, though there’s usually some kind of “tell” that a human can spot. But the Canvas app isn’t trying to make something indistinguishable from reality — as concept artist Jama Jurabaev explains in the video below, it’s more about being able to experiment freely with imagery more detailed than a doodle.
For instance, if you want to have a moldering ruin in a field with a river off to one side, a quick pencil sketch can only tell you so much about what the final piece might look like. What if you have it one way in your head, and then two hours of painting and coloring later you realize that because the sun is setting on the left side of the painting, it makes the shadows awkward in the foreground?
If instead you just scribbled these features into Canvas, you might see that this was the case right away, and move on to the next idea. There are even ways to quickly change the time of day, palette, and other high-level parameters so they can quickly be evaluated as options.
“I’m not afraid of blank canvas any more,” said Jurabaev. “I’m not afraid to make very big changes, because I know there’s always AI helping me out with details… I can put all my effort into the creative side of things, and I’ll let Canvas handle the rest.”
It’s very like Google’s Chimera Painter, if you remember that particular nightmare fuel, in which an almost identical process was used to create fantastic animals. Instead of snow, rock and bushes, it had hind leg, fur, teeth and so on, which made it rather more complicated to use and easy to go wrong with.
Still, it may be better than the alternative, for certainly an amateur like myself could never draw even the weird tube-like animals that resulted from basic blob painting.
Unlike the Chimera Creator, however, this app is run locally, and requires a beefy Nvidia video card to do it. GPUs have long been the hardware of choice for machine learning applications, and something like a real-time GAN definitely needs a chunky one. You can download the app for free here.
How one founder realized satellite internet didn’t have to be fast or expensive to be useful
It’s hard to understand just how steeply the cost of launching and operating satellites has dropped, particularly since the introduction of lower cost launch services from a number of commercial players, and the maturation of the smartphone supply chain. Swarm co-founder and CEO realized just how much the cost curve had changed when she and her co-founder Ben Longmeir realized that they could outfit tiny satellites Longmeir had created as a kind of space lover’s hobby with the equipment needed to provide low-bandwidth connectivity to low-powered devices around the world.
In this week’s episode of Found, Sara walks us through how she went from an engineering career that included stints at NASA’s Jet Propulsion Laboratory and Google, to building Swarm as a first-time founder and CEO. We covered a range of topics including how Sara and Ben decided who would be CEO, what it’s like leading a small but growing team, and how to evaluate your decisions as a founder, and commit to a course of action to move forward.
Sara was extremely candid with us about her experience as a founder and CEO, and this is definitely one of our most open and honest conversations to date.
We loved our time chatting with Sara, and we hope you love yours listening to the episode. And of course, we’d love if you can subscribe to Found in Apple Podcasts, on Spotify, on Google Podcasts or in your podcast app of choice. Please leave us a review and let us know what you think, or send us direct feedback either on Twitter or via email at email@example.com. And please join us again next week for our next featured founder.
As clinical guidelines shift, heart disease screening startup pulls in $43M Series B
Cleerly Coronary, a company that uses A.I powered imaging to analyze heart scans, announced a $43 million Series B funding this week. The funding comes at a moment when it seems that a new way of screening for heart disease is on its way.
Cleerly was started in 2017 by James K. Min a cardiologist, and the director of the Dalio Institute for Cardiac Imaging at New York Presbyterian Hospital/Weill Cornell Medical College. The company, which uses A.I to analyze detailed CT scans of the heart, has 60 employees, and has raised $54 million in total funding.
The Series B round was led by Vensana Capital, but also included LVR Health, New Leaf Venture Partners, DigiTx Partners, and Cigna Ventures.
The startup’s aim is to provide analysis of detailed pictures of the human heart that have been examined by artificial intelligence. This analysis is based on images taken via Cardiac Computer Tomography Angiogram (CTA), a new, but rapidly growing manner of scanning for plaques.
“We focus on the entire heart, so every artery, and its branches, and then atherosclerosis characterization and quantification,” says Min. “We look at all of the plaque buildup in the artery, [and] the walls of the artery, which historical and traditional methods that we’ve used in cardiology have never been able to do.”
Cleerly is a web application, and it requires that a CTA image specifically, which the A.I. is trained to analyze, is actually taken when patients go in for a checkup.
When a patient goes in for a heart exam after experiencing a symptom like chest pain, there are a few ways they can be screened. They might undergo a stress test, an echocardiogram (ECG), or a coronary angiogram – a catheter and x-ray-based test. CTA is a newer form of imaging in which a scanner takes detailed images of the heart, which is illuminated with an injected dye.
Cleerly’s platform is designed to analyze those CTA images in detail, but they’ve only recently become a first-line test (a go-to, in essence) when patients come in with suspected heart problems. The European Society of Cardiology updated guidelines to make CTA a first-line test in evaluating patients with chronic coronary disease. In the UK, it became a first-line test in the evaluation of patients with chest pain in 2016.
CTA is already used in the US, but guidelines may expand how often it’s actually used. A review on CTA published on the American College of Cardiology website notes that it shows “extraordinary potential.”
There’s movement on the insurance side, too. In 2020, United Healthcare announced the company will now reimburse for CTA scans when they’re ordered to examine low-to medium risk patients with chest pain. Reimbursement qualification is obviously a huge boon to broader adoption.
CTA imaging might not be great for people who already have stents in their hearts, or, says Min, those who are just in for a routine checkup (there is low-dose radiation associated with a CTA scan). Rather, Cleerly will focus on patients who have shown symptoms or are already at high risk for heart disease.
The CDC estimates that currently 18.2 million adults currently have coronary artery heart disease (the most common kind), and that 47 percent of Americans have one of the three most prominent risk factors for the disease: high blood pressure, high cholesterol, or a smoking habit.
These shifts (and anticipated shifts) in guidelines suggest that a lot more of these high-risk patients may be getting CTA scans in the future, and Cleerly has been working on mining additional information from them in several large-scale clinical trials.
There are plenty of different risk factors that contribute to heart disease, but the most basic understanding is that heart attacks happen when plaques build up in the arteries, which narrows the arteries and constricts the flow of blood. Clinical trials have suggested that the types of plaques inside the body may contain information about how risky certain blockages are compared to others beyond just much of the artery they block.
A trial on 25,251 patients found that, indeed, the percentage of construction in the arteries increases the risk of heart attack. But the type of plaque in those arteries identified high-risk patients better than other measures. Patients who went on to have sudden heart attacks, for example, tended to have higher levels of fibrofatty or necrotic core plaque in their hearts.
These results do suggest that it’s worth knowing a bit more detail about plaque in the heart. Note that Min is an author of this study, but it was also conducted at 13 different medical centers.
As with all A.I based diagnostic tools the big question is: How well does it actually recognize features within a scan?
At the moment FDA documents emphasize that it is not meant to supplant a trained medical professional who can interpret the results of a scan. But tests have suggested it fares pretty well.
A June 2021 study compared Cleerly’s A.I analysis of CTA scans to that of three expert readers, and found that the A.I had a diagnostic accuracy of about 99.7 percent when evaluating patients who had severe narrowing in their arteries. Three of nine study authors hold equity in Cleerly.
With this most recent round of funding, Min says he aims to pursue more commercial partnerships and scale up to meet the existing demand. “We have sort of stayed under the radar, but we came above the radar because now I think we’re prepared to fulfill demand,” he says.
Still, the product itself will continue to be tested and refined. Cleerly is in the midst of seven performance indication studies that will evaluate just how well the software can spot the litany of plaques that can build up in the heart.
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