Last week, Kathryn Zealand shared some insight on the eve of Women’s Equality Day. The post highlighted an issue that’s been apparent to everyone in and around the robotics industry: there’s a massive gender gap. It’s something we try to be mindful of, particularly when programming events like TC Sessions: Robotics. Zealand cites some pretty staggering figures in the piece.
According to the stats, around 9% of robotics engineers are female. That’s bad. That’s, like, bad even by the standards of STEM fields in general — which is to say, it’s really, really bad. (The ethnic disparities in the same source are worth drawing attention to, as well.)
Zealand’s piece was published on LinkedIn — fitting, given that the overarching focus here is on hiring. Well worth your time, if you’re involved in the hiring process at a robotics firm and are concerned about broader diversity issues (which hopefully go hand in hand for most orgs). Zealand offers some outside of the box thinking in terms of what, precisely, it means to be a roboticist, writing:
We have a huge opportunity here! Women and other under-represented groups are untapped pools of talented people who, despite not thinking of themselves as “roboticists,” could be vital members of a world-changing robotics team.
I’m going to be real with you for a minute, and note what really caught my eye was that above image. See, Zealand is a Project Lead at Alphabet X. And what you have there is a robotic brace — or, rather, what appears to be a component of a soft exosuit.
Image Credits: Bryce Durbin/TechCrunch
Exosuits/exoskeletons are a booming category for robotics right now that really run the gamut from Sarcos’ giant James Cameron-esque suit to far subtler, fabric-based systems. Some key names in the space include Ekso Bionics, ReWalk and SuitX. Heck, even Samsung has shown off a solution as part of a robotics department that appears to be largely ornamental at the moment.
Image Credits: Harvard Biodesign Lab
Most of these systems aim to tackle one of two issues: 1) Augmenting workers to assist with difficult or repetitive tasks for work and 2) Provide assistance to those with impaired mobility. Many companies have offers for both. Here’s what Harvard’s Biodesign Lab has to say on the matter:
As compared to a traditional exoskeleton, these systems have several advantages: the wearer’s joints are unconstrained by external rigid structures, and the worn part of the suit is extremely light. These properties minimize the suit’s unintentional interference with the body’s natural biomechanics and allow for more synergistic interaction with the wearer.
Alphabet loves to give the occasional behind-the-scenes peak at some of its X projects, and it turns out we’ve had a couple of glimpses of the Smarty Pants project. Zealand and Smarty Pants make a cameo in a Wired UK piece that ran early last year about the 10th anniversary of Google/Alphabet X. The piece notes that that the project was inspired by her experience with her 92-year-old grandmother’s mobility issues.
Image Credits: Alphabet X
The piece highlights a very early Raspberry Pi-controlled setup created by a team that includes costume designers and deep learning specialists (getting back to that earlier discussion about outside the box thinking when it comes to what constitutes a roboticist). The system is using sensors in an attempt to effectively predict movement in order to anticipate where force needs to be applied for tasks like walking up stairs. The piece ends on a fittingly somber note, “Fewer than half of X’s investigations become Projects. By the time this story is published it will probably have been killed.”
My suspicion is that the team is looking to differentiate itself from other exosuit projects by leveraging Google’s knowledge base of deep learning and AI to build out those predictive algorithms.
Alphabet declined to offer additional information on the project, noting that it likes to give its moonshot teams, “time to learn and iterate out of the spotlight.” But last October, we got what is probably our best look at Smarty Pants, in the form of a video highlighting Design Kitchen, Alphabet X’s lab/design studio.
Image Credits: Alphabet X
The Wired piece mentions a “pearlescent bumbag,” holding the aforementioned Raspberry Pi and additional components. For you yanks, that’s a fanny pack, which are not referred to as such in the U.K., owing to certain regional slang. Said fanny pack also makes an appearance in the video, providing, honestly, a very clever solution to the issue of hanging wires for an early-stage wearable prototype.
“One of the things that’s really helped the team is being really focused on a problem. Even if you spent months on something, if it’s not actually going to achieve that goal, then sometimes you honor the work that’s been done and say, ‘we’ve learned a ton of things during the process, but this is not the one that’s actually going to solve that problem.’ ”
The most notable takeaway from the video is some additional footage of prototypes. One imagines that, by the time Alphabet feels confident sharing that sort of stuff with the world, the team has moved well beyond it. “It doesn’t matter how janky and cardboard-and-duct-tape it is, as long as it helps you learn — and everyone can prototype, even while working from home,” the X team writes in an associated blog post.
The one other bit of information we have at the moment is a granted patent application from last year, which comes with all of the standard patent warnings. Seeing a patent come to fruition is often even more of a longshot (read: moonshot) than betting on an Alphabet X project to graduate. But they can offer some insight into where a team is headed — or at least some of the avenues it has considered.
Image Credits: Alphabet X
The patent highlights similar attempts to anticipate movement as those highlighted above. It effectively uses sensors and machine learning to adjust the tension on regions of the garments designed to assist the wearer.
Image Credits: Alphabet X
The proposed methods and systems provide adaptive support and assistance to users by performing intelligent dynamic adjustment of tension and stiffness in specific areas of fabric or by applying forces to non-stretch elements within a garment that is comfortable enough to be suitable for frequent, everyday usage. The methods include detecting movement of a particular part of a user’s body enclosed within the garment, determining an activity classification for that movement, identifying a support configuration for the garment tailored to the activity classification, and dynamically adjusting a tension and/or a stiffness of one or more controllable regions of the garment or applying force to non-stretch fabric elements in the garment to provide customized support and assistance for the user and the activity the user is performing.
It’s nice seeing Alphabet take a more organic approach to developing robotics startups in-house, rather than the acquisitions and consolidations that occurred several years back that ultimately found Boston Dynamics briefly living under the Google umbrella. Of course, we saw the recent graduation of the Wendy Tan White-led Intrinsic, which builds software for industrial robotics.
All right, so there’s a whole bunch of words about a project we know next to nothing about! Gotta love the startup space, where we’re definitely not spinning wild speculation based on a thin trail of breadcrumbs.
I will say for sure that I definitely know more about Agility Robotics than I did this time last week, after speaking with the Oregon-based company’s CEO and CTO. The conversation was ostensibly about a new video the team released showcasing Digit doing some menial tasks in a warehouse/fulfillment setting.
Some key things I learned:
Image Credits: Agility Robotics
Oh, and a good quote about job loss from CEO Damion Shelton:
The conversation around automation has shifted a bit. It’s viewed as an enabling technology to allow you to keep the workforce that you have. There are a lot of conversations around the risks of automation and job loss, but the job loss is actually occurring now, in advance of the automated solutions.
Agility hopes to start rolling out its robots to locations in the next year. More immediate than that, however, is this deal between Simbe Robotics and midwestern grocery chain, Schnuks. The food giant will be bringing Simbe’s inventor robots to all of its 111 stores, four years after it began piloting the tech.
Schnuck Markets deploys Tally robot by Simbe Robotics to its stores – bringing shelf insights for better shopping experience. Photographed on Friday, Aug. 13, 2021, in Des Peres, Mo.
Simbe says its Tally robot can reduce out of stock items by 20-30% and detect 14x more missing inventor than standard human scanning.
Carbon Robotics (not to be confused with the prosthetic company of the same name that made it onto our Hardware Battlefield a few years back) just raised $27 million. The Series B brings its total funding to around $36 million. The Seattle-based firm builds autonomous robots that zap weeds with lasers. We highlighted their most recent robot in this column back in April.
And seeing how we recently updated you on iRobot’s continued indefinite delay for the Terra, here’s a new robotic mower from Segway-Ninebot.
Image Credits: Segway-Ninebot
Segway’s first robotic lawnmower is designed for a lawn area of up to 3,000 square meters, has several features of a smart helper in the garden and is the quietest mower on the market with only 54 dB. The Frequent Soft Cut System (FSCS) ensures that the lawn is cut from above and the desired height is reached gradually. Offset blades allow cutting as close as possible to edges and corners.
That’s it for the week. Don’t forget to sign up to get the upcoming free newsletter version of Actuator delivered to your inbox.
Explosion, a company that has combined an open source machine learning library with a set of commercial developer tools, announced a $6 million Series A today on a $120 million valuation. The round was led by SignalFire, and the company reported that today’s investment represents 5% of its value.
Oana Olteanu from SignalFire will be joining the board under the terms of the deal, which includes warrants of $12 million in additional investment at the same price.
“Fundamentally, Explosion is a software company and we build developer tools for AI and machine learning and natural language processing. So our goal is to make developers more productive and more focused on their natural language processing, so basically understanding large volumes of text, and training machine learning models to help with that and automate some processes,” company co-founder and CEO Ines Montani told me.
The company started in 2016 when Montani met her co-founder, Matthew Honnibal in Berlin where he was working on the spaCy open source machine learning library. Since then, that open source project has been downloaded over 40 million times.
In 2017, they added Prodigy, a commercial product for generating data for the machine learning model. “Machine learning is code plus data, so to really get the most out of the technologies you almost always want to train your models and build custom systems because what’s really most valuable are problems that are super specific to you and your business and what you’re trying to find out, and so we saw that the area of creating training data, training these machine learning models, was something that people didn’t pay very much attention to at all,” she said.
The next step is a product called Prodigy Teams, which is a big reason the company is taking on this investment. “Prodigy Teams is [a hosted service that] adds user management and collaboration features to Prodigy, and you can run it in the cloud without compromising on what people love most about Prodigy, which is the data privacy, so no data ever needs to get seen by our servers,” she said. They do this by letting the data sit on the customer’s private cluster in a private cloud, and then use Prodigy Team’s management features in the public cloud service.
Today, they have 500 customers using Prodigy including Microsoft and Bayer in addition to the huge community of millions of open source users. They’ve built all this with just 17 people, even as they continue to slowly add employees, expecting to reach 20 by the end of the year.
She believes if you’re thinking too much about diversity in your hiring process, you probably have a problem already. “If you go into hiring and you’re thinking like, oh, how can I make sure that the way I’m hiring is diverse, I think that already shows that there’s maybe a problem,” she said.
“If you have a company, and it’s 50 dudes in their 20s, it’s not surprising that you might have problems attracting people who are not white dudes in their 20s. But in our case, our strategy is to hire good people and good people are often very diverse people, and again if you play by the [startup] playbook, you could be limited in a lot of other ways.”
She said that they have never seen themselves as a traditional startup following some conventional playbook. “We didn’t raise any investment money [until now]. We grew the team organically, and we focused on being profitable and independent [before we got outside investment],” she said.
But more than the money, Montani says that they needed to find an investor that would understand and support the open source side of the business, even while they got capital to expand all parts of the company. “Open source is a community of users, customers and employees. They are real people, and [they are not] pawns in [some] startup game, and it’s not a game. It’s real, and these are real people,” she said.
“They deserve more than just my eyeballs and grand promises. […] And so it’s very important that even if we’re selling a small stake in our company for some capital [to build our next] product [that open source remains at] the core of our company and that’s something we don’t want to compromise on,” Montani said.
How many of us have not switched insurance carriers because we don’t want to deal with the hassle of comparison shopping?
A lot, I’d bet.
Today, Insurify, a startup that wants to help people make it easier to get better rates on home, auto and life insurance, announced that it has closed $100 million in an “oversubscribed” Series B funding round led by Motive Partners.
Existing backers Viola FinTech, MassMutual Ventures, Nationwide, Hearst Ventures and Moneta VC also put money in the round, as well as new investors Viola Growth and Fort Ross Ventures. With the new financing, Cambridge, Massachusetts-based Insurify has now raised a total of $128 million since its 2013 inception. The company declined to disclose the valuation at which the money was raised.
Since we last covered Insurify, the startup has seen some impressive growth. For example, it has seen its new and recurring revenue increase by “6x” since it closed its Series A funding in the 2019 fourth quarter. Over the last three years, Insurify has achieved a CAGR (compound annual growth rate) of 151%, according to co-founder and CEO Snejina Zacharia. It has also seen consistent “2.5x” year-over-year revenue growth, she said.
Insurify has built a machine learning-based virtual insurance agent that integrates with more than 100 carriers to digitize — and personalize — the insurance shopping experience. There are others in the insurtech space, but none that we know of currently tackling home, auto and life insurance. For example, Jerry, which has raised capital twice this year, is focused mostly on auto insurance, although it does have a home product. The Zebra, which became a unicorn this year, started out as a site for people looking for auto insurance via its real-time quote comparison tool. Over time, it has also evolved to offer homeowners insurance with the goal of eventually branching out into renters and life insurance. But it too is mostly focused on auto.
Zacharia said that since Insurify’s Series A funding, it has expanded its home insurance marketplace, deepened its carrier integrations to provide users an “instant” purchase experience and launched its first two embedded insurance products through partnerships with Toyota Insurance Management Solutions and Nationwide (the latter of which also participated in the Series B funding round).
Image Credits: Insurify
Last year, when ShyScanner had to lay off staff, Insurify scooped up much of its engineering team and established an office in Sofia, Bulgaria.
Zacharia, a former Gartner executive, was inspired to start the company after she was involved in a minor car accident while getting her MBA at MIT. The accident led to a spike in her insurance premium and Zacharia was frustrated by the “complex and cumbersome” experience of car insurance shopping. She teamed up with CTO Tod Kiryazov to build Insurify, which the pair describe as a virtual insurance agent that offers real-time quotes.
“We decided to build the most trusted virtual insurance agent in the industry that allows for customers to easily search, compare and buy fully digitally — directly from their mobile phone, or desktop, and really get a very smart, personalized experience based on their unique preferences,” Zacharia told TechCrunch. “We leverage artificial intelligence to be able to make recommendations on both coverage as well as carrier selection.”
Notably, Insurify is also a fully licensed agent that takes over the fulfillment and servicing of the policies. Since the company is mostly working as an insurance agent, it gets paid new and renewed commission. So while it’s not a SaaS business, its embedded insurance offerings have SaaS-like monetization.
“Our goal is to provide an experience for the end consumer that allows them to service and manage all of their policies in one place, digitally,” Zacharia said. “We think that the data recommendations that the platform provides can really remove most of the friction that currently exists in the shopping experience.”
Insurify plans to use its fresh capital to continue to expand its operations and accelerate its growth plans. It also, naturally, wants to add to its 125-person team.
“We want to build into our API integrations so customers can receive real-time direct quotes with better personalization and a more tailored experience,” Kiryazov said. “We also want to identify more embedded insurance opportunities and expand the product functionality.”
The company also down the line wants to expand into other verticals such as pet insurance, for example.
Insurify intends to use the money in part to build brand awareness, potentially through TV advertising.
“Almost half of our revenue comes from self-directed traffic,” Zacharia said. “So we want to explore more inorganic growth.”
James “Jim” O’Neill, founding partner at Motive Partners and partner Andy Rear point out that online purchasing now accounts for almost all of the growth in U.S. auto insurance.
“The lesson from other markets which have been through this transition is that customers prefer choice, presented as a simple menu of products and prices from different insurers, and a straightforward online purchasing process,” they wrote via email. “The U.S. auto market is huge: even a slow transition to online means a massive opportunity for Insurify.”
In conducting their due diligence, the pair said they were impressed with how the startup is building a business model “that works for customers, insurers and white-label partners.”
Harel Beit-On, founder and general partner at Viola Growth, believes that the quantum leap in e-commerce due to COVID-19 will completely transform the buying experience in almost every sector, including insurance.
“It is time to bring the frictionless purchasing experience that customers expect to the insurance space as well,” she said. “Following our fintech fund’s recent investment in the company, we watched Insurify’s immense growth, excellent execution with customer acquisition and building a brand consumers trust.”
In the customer service industry, your accent dictates many aspects of your job. It shouldn’t be the case that there’s a “better” or “worse” accent, but in today’s global economy (though who knows about tomorrow’s) it’s valuable to sound American or British. While many undergo accent neutralization training, Sanas is a startup with another approach (and a $5.5 million seed round): using speech recognition and synthesis to change the speaker’s accent in near real time.
The company has trained a machine learning algorithm to quickly and locally (that is, without using the cloud) recognize a person’s speech on one end and, on the other, output the same words with an accent chosen from a list or automatically detected from the other person’s speech.
It slots right into the OS’s sound stack so it works out of the box with pretty much any audio or video calling tool. Right now the company is operating a pilot program with thousands of people in locations from the U.S. and U.K. to the Philippines, India, Latin America and others. Accents supported will include American, Spanish, British, Indian, Filipino and Australian by the end of the year.
To tell the truth, the idea of Sanas kind of bothered me at first. It felt like a concession to bigoted people who consider their accent superior and think others below them. Tech will fix it … by accommodating the bigots. Great!
But while I still have a little bit of that feeling, I can see there’s more to it than this. Fundamentally speaking, it is easier to understand someone when they speak in an accent similar to your own. But customer service and tech support is a huge industry and one primarily performed by people outside the countries where the customers are. This basic disconnect can be remedied in a way that puts the onus of responsibility on the entry-level worker, or one that puts it on technology. Either way the difficulty of making oneself understood remains and must be addressed — an automated system just lets it be done more easily and allows more people to do their job.
It’s not magic — as you can tell in this clip, the character and cadence of the person’s voice is only partly retained and the result is considerably more artificial sounding:
But the technology is improving and like any speech engine, the more it’s used, the better it gets. And for someone not used to the original speaker’s accent, the American-accented version may very well be more easily understood. For the person in the support role, this likely means better outcomes for their calls — everyone wins. Sanas told me that the pilots are just starting so there are no numbers available from this deployment yet, but testing has suggested a considerable reduction of error rates and increase in call efficiency.
It’s good enough at any rate to attract a $5.5 million seed round, with participation from Human Capital, General Catalyst, Quiet Capital and DN Capital.
“Sanas is striving to make communication easy and free from friction, so people can speak confidently and understand each other, wherever they are and whoever they are trying to communicate with,” CEO Maxim Serebryakov said in the press release announcing the funding. It’s hard to disagree with that mission.
While the cultural and ethical questions of accents and power differentials are unlikely to ever go away, Sanas is trying something new that may be a powerful tool for the many people who must communicate professionally and find their speech patterns are an obstacle to that. It’s an approach worth exploring and discussing even if in a perfect world we would simply understand one another better.
Heroes, one of the new wave of startups aiming to build big e-commerce businesses by buying up smaller third-party merchants on Amazon’s Marketplace, has raised another big round of funding to double down on that strategy. The London startup has picked up $200 million, money that it will mainly be using to snap up more merchants. Existing brands in its portfolio cover categories like babies, pets, sports, personal health and home and garden categories — some of them, like PremiumCare dog chews, the Onco baby car mirror, gardening tool brand Davaon and wooden foot massager roller Theraflow, category best-sellers — and the plan is to continue building up all of these verticals.
Crayhill Capital Management, a fund based out of New York, is providing the funding, and Riccardo Bruni — who co-founded the company with twin brother Alessio and third brother Giancarlo — said that the bulk of it will be going toward making acquisitions, and is therefore coming in the form of debt.
Raising debt rather than equity at this point is pretty standard for companies like Heroes. Heroes itself is pretty young: it launched less than a year ago, in November 2020, with $65 million in funding, a round comprised of both equity and debt. Other investors in the startup include 360 Capital, Fuel Ventures and Upper 90.
Heroes is playing in what is rapidly becoming a very crowded field. Not only are there tens of thousands of businesses leveraging Amazon’s extensive fulfillment network to sell goods on the e-commerce giant’s marketplace, but some days it seems we are also rapidly approaching a state of nearly as many startups launching to consolidate these third-party sellers.
Many a roll-up play follows a similar playbook, which goes like this: Amazon provides the marketplace to sell goods to consumers, and the infrastructure to fulfill those orders, by way of Fulfillment By Amazon and its Prime service. Meanwhile, the roll-up business — in this case Heroes — buys up a number of the stronger companies leveraging FBA and the marketplace. Then, by consolidating them into a single tech platform that they have built, Heroes creates better economies of scale around better and more efficient supply chains, sharper machine learning and marketing and data analytics technology, and new growth strategies.
What is notable about Heroes, though — apart from the fact that it’s the first roll-up player to come out of the U.K., and continues to be one of the bigger players in Europe — is that it doesn’t believe that the technology plays as important a role as having a solid relationship with the companies it’s targeting, key given that now the top marketplace sellers are likely being feted by a number of companies as acquisition targets.
“The tech is very important,” said Alessio in an interview. “It helps us build robust processes that tie all the systems together across multiple brands and marketplaces. But what we have is very different from a SaaS business. We are not building an app, and tech is not the core of what we do. From the acquisitions side, we believe that human interactions ultimately win. We don’t think tech can replace a strong acquisition process.”
Image Credits: Heroes
Heroes’ three founder-brothers (two of them, Riccardo and Alessio, pictured above) have worked across a number of investment, finance and operational roles (the CVs include Merrill Lynch, EQT Ventures, Perella Weinberg Partners, Lazada, Nomura and Liberty Global) and they say there have been strong signs so far of its strategy working: of the brands that it has acquired since launching in November, they claim business (sales) has grown five-fold.
Collectively, the roll-up startups are raising hundreds of millions of dollars to fuel these efforts. Other recent hopefuls that have announced funding this year include Suma Brands ($150 million); Elevate Brands ($250 million); Perch ($775 million); factory14 ($200 million); Thrasio (currently probably the biggest of them all in terms of reach and money raised and ambitions), Heyday, The Razor Group, Branded, SellerX, Berlin Brands Group (X2), Benitago, Latin America’s Valoreo and Rainforest and Una Brands out of Asia.
The picture that is emerging across many of these operations is that many of these companies, Heroes included, do not try to make their particular approaches particularly more distinctive than those of their competitors, simply because — with nearly 10 million third-party sellers today on Amazon globally — the opportunity is likely big enough for all of them, and more, not least because of current market dynamics.
“It’s no secret that we were inspired by Thrasio and others,” Riccardo said. “Combined with COVID-19, there has been a massive acceleration of e-commerce across the continent.” It was that, plus the realization that the three brothers had the right e-commerce, fundraising and investment skills between them, that made them see what was a ‘perfect storm’ to tackle the opportunity, he continued. “So that is why we jumped into it.”
In the case of Heroes, while the majority of the funding will be used for acquisitions, it’s also planning to double headcount from its current 70 employees before the end of this year with a focus on operational experts to help run their acquired businesses.
Zendesk is looking to grow its customer service capabilities, and today it announced the acquisition of early-stage artificial intelligence startup Cleverly.
Financial terms of the deal are not being publicly disclosed at this time and Cleverly has not been entirely public about the size of its funding. Founded in 2019, Cleverly is based in Lisbon, Portugal and, according to its site, has received funding from the European Union’s Horizon 2020 research and innovation programme.
The startup was also listed by TechCrunch in an article earlier this year looking at the startup scene in Lisbon as being one of the most exciting deep tech companies in the region, according to Stephan Morais, partner at Indico Capital Partners.
Cleverly’s product platform provides a series of artificial intelligence-powered capabilities, including a triage function to automatically tag incoming service requests to help categorize workflow. The startup also has what it refers to as AI-powered human augmentation with its agent assist capability that aims to help customer service agents provide the right answers to inquiries. The company’s technology already integrates with Zendesk, as well as with Salesforce.
As to why Zendesk is acquiring Cleverly, Shawna Wolverton, EVP of product at Zendesk, noted in an email to TechCrunch that the two companies have a similar vision for the future of customer service.
“Cleverly and Zendesk want to democratize AI, so companies can create practical applications that make it possible for businesses to get started with AI right out of the box — without a team of data scientists required,” she said.
Wolverton added that AI has the ability to help customer experience teams deliver great customer service. She expects that the next generation of great customer experiences will be created by intelligent software, enabling humans and AI working closely together to deliver this at scale.
Wolverton noted that her company will be welcoming all of Cleverly’s team to Zendesk beginning August 30, including founders Christina Fonseca as VP of Product and Pedro Coelho as principal engineering lead, Machine Learning.
Zendesk already has a series of AI-enabled capabilities that can help organizations automate customer conversations, boost agent productivity and increase operational efficiency, including the Answer Bot, which is a chatbot for customer interactions providing answers pulled from Zendesk’s knowledge base. Zendesk’s Content Cues AI-powered feature in turn helps to automatically review support tickets and also can identify areas where content in a company’s help center can be updated to be more useful to users.
“With Cleverly, we will deliver a range of capabilities that automate key insights, further reduce manual tasks and improve workflows, and overall lead to happier, more productive support teams,” Wolverton said. “We will have more news to share on that front once the team is up and running.
Zendesk’s business has been growing in 2021 overall, reporting second-quarter fiscal 2021 revenue of $318.2 million for a 29% year-over-year gain.
A new startup called Popcorn wants to make work communication more fun and personal by offering a way for users to record short video messages, or “pops,” that can be used for any number of purposes in place of longer emails, texts, Slack messages or Zoom calls. While there are plenty of other places to record short-form video these days, most of these exist in the social media space, which isn’t appropriate for a work environment. Nor does it make sense to send a video you’ve recorded on your phone as an email attachment, when you really just want to check in with a colleague or say hello.
Popcorn, on the other hand, lets you create the short video and then send a URL to that video anywhere you would want to add a personal touch to your message.
For example, you could use Popcorn in a business networking scenario, where you’re trying to connect with someone in your industry for the first time — aka “cold outreach.” Instead of just blasting them a message on LinkedIn, you could also paste in the Popcorn URL to introduce yourself in a more natural, friendly fashion. You also could use Popcorn with your team at work for things like daily check-ins, sharing progress on an ongoing project or to greet new hires, among other things.
Image Credits: Popcorn
Videos themselves can be up to 60 seconds in length — a time limit designed to keep Popcorn users from rambling. Users also can opt to record audio only if they don’t want to appear on video. And you can increase the playback speed if you’re in a hurry. Users who want to receive “pops” could also advertise their “popcode” (e.g. try mine at U8696).
The idea to bring short-form video to the workplace comes from Popcorn co-founder and CEO Justin Spraggins, whose background is in building consumer apps. One of his first apps to gain traction back in 2014 was a Tinder-meets-Instagram experience called Looksee that allowed users to connect around shared photos. A couple years later, he co-founded a social calling app called Unmute, a Clubhouse precursor of sorts. He then went on to co-found 9 Count, a consumer app development shop which launched more social apps like BFF (previously Wink) and Juju.
9 Count’s lead engineer, Ben Hochberg, is now also a co-founder on Popcorn (or rather, Snack Break, Inc. as the legal entity is called). They began their work on Popcorn in 2020, just after the start of the COVID-19 pandemic. But the rapid shift to remote work in the days that followed could now help Popcorn gain traction among distributed teams. Today’s remote workers may never again return to in-person meetings at the office, but they’re also growing tired of long days stuck in Zoom meetings.
With Popcorn, the goal is to make work communication fun, personal and bite-sized, Spraggins says. “[We want to] bring all the stuff we’re really passionate about in consumer social into work, which I think is really important for us now,” he explains.
“You work with these people, but how do you — without scheduling a Zoom — how do you bring the ‘human’ to it?,” Spraggins says. “I’m really excited about making work products feel more social, more like Snapchat than utility tools.”
There is a lot Popcorn would still need to figure out to truly make a business-oriented social app work, including adding enhanced security, limiting spam, offering some sort of reporting flow for bad actors, and more. It will also eventually need to land on a successful revenue model.
Currently, Popcorn is a free download on iPhone, iPad and Mac, and offers a Slack integration so you can send video messages to co-workers directly in the communication software you already use to catch up and stay in touch. The app today is fairly simple, but the company plans to enhance its short videos over time using AR frames that let users showcase their personalities.
The startup raised a $400,000 pre-seed round from General Catalyst (Nico Bonatsos) and Dream Machine (Alexia Bonatsos, previously editor-in-chief at TechCrunch.) Spraggins says the company will be looking to raise a seed round in the fall to help with hires, including in the AR space.
“Even with its vast local talent, it seems Israel still has many hurdles to overcome in order to become a global fintech hub. [ … ] Having that said, I don’t believe any of these obstacles will prevent Israel from generating disruptive global fintech startups that will become game-changing businesses.”
I wrote that back in 2018, when I was determined to answer whether Israel had the potential to become a global fintech hub. Suffice to say, this prediction from three years ago has become a reality.
In 2019, Israeli fintech startups raised over $1.8 billion; in 2020, they were said to have raised $1.48 billion despite the pandemic. Just in the first quarter of 2021, Israeli fintech startups raised $1.1 billion, according to IVC Research Center and Meitar Law Offices.
It’s then no surprise that Israel now boasts over a dozen fintech unicorns in sectors such as payments, insurtech, lending, banking and more, some of which reached the desired status just in the beginning of 2021 — like Melio and Papaya Global, which raised $110 million and $100 million, respectively.
Over the years I’ve been fortunate to invest (both as a venture capitalist and personally) in successful early-stage fintech companies in the U.S., Israel and emerging markets — Alloy, Eave, MoneyLion, Migo, Unit, AcroCharge and more.
The major shifts and growth of fintech globally over these years has been largely due to advanced AI-based technologies, heightened regulatory scrutiny, a more innovative and adaptive approach among financial institutions to build partnerships with fintechs, and, of course, the COVID pandemic, which forced consumers to transact digitally.
The pandemic pushed fintechs to become essential for business survival, acting as the main contributor of the rapid migration to digital payments.
So what is it about Israeli-founded fintech startups that stand out from their scaling neighbors across the pond? Israeli founders first and foremost have brought to the table a distinct perspective and understanding of where the gaps exist within their respective focus industries — whether it was Hippo and Lemonade in the world of property and casualty insurance, Rapyd and Melio in the world of business-to-business payments, or Earnix and Personetics in the world of banking data and analytics.
This is even more compelling given that many of these Israeli founders did not grow within financial services, but rather recognized those gaps, built their know-how around the industry (in some cases by hiring or partnering with industry experts and advisers during their ideation phase, strengthening their knowledge and validation), then sought to build more innovative and customer-focused solutions than most financial institutions can offer.
Having this in mind, it is becoming clearer that the Israeli fintech industry has slowly transitioned into a mature ecosystem with a combination of local talent, which now has expertise from a multitude of local fintechs that have scaled to success; a more global network of banking and insurance partners that have recognized the Israeli fintech disruptors; and the smart fintech -focused venture capital to go along with it. It’s a combination that will continue to set up Israeli fintech founders for success.
In addition, a major contributor to the fintech industry comes from the technological side. It is never enough to reach unicorn status with just the tech on the back end.
What most likely differentiates Israeli fintech from other ecosystems is the strong technological barriers and infrastructure built from the ground up, which then, of course, leads to the ability to be more customized, compliant, secured, etc. If I had to bet on where I believe Israeli fintech startups could become market leaders, I’d go with the following.
Voice technologies have come a long way over the years; where once you knew you were talking to a robot, now financial institutions and applications offer a fully automated experience that sounds and feels just like a company employee.
Israel has shown growing success in the world of voice tech, with companies like Gong.io providing insights for remote sales teams; Bonobo (acquired by Salesforce) offering insights from customer support calls, texts and other interactions; and Voca.ai (acquired by Snapchat) offering an automated support agent to replace the huge costs of maintaining call centers.
Finding the right learning platform can be difficult, especially as companies look to upskill and reskill their talent to meet demand for certain technological capabilities, like data science, machine learning and artificial intelligence roles.
Workera.ai’s approach is to personalize learning plans with targeted resources — both technical and nontechnical roles — based on the current level of a person’s proficiency, thereby closing the skills gap.
The Palo Alto-based company secured $16 million in Series A funding, led by New Enterprise Associates, and including existing investors Owl Ventures and AI Fund, as well as individual investors in the AI field like Richard Socher, Pieter Abbeel, Lake Dai and Mehran Sahami.
Kian Katanforoosh, Workera’s co-founder and CEO, says not every team is structured or feels supported in their learning journey, so the company comes at the solution from several angles with an assessment on mentorship, where the employee wants to go in their career and what skills they need for that, and then Workera will connect those dots from where the employee is in their skillset to where they want to go. Its library has more than 3,000 micro-skills and personalized learning plans.
“It is what we call precision upskilling,” he told TechCrunch. “The skills data then can go to the organization to determine who are the people that can work together best and have a complementary skill set.”
Workera was founded in 2020 by Katanforoosh and James Lee, COO, after working with Andrew Ng, Coursera co-founder and Workera’s chairman. When Lee first connected with Katanforoosh, he knew the company would be able to solve the problem around content and basic fundamentals of upskilling.
It raised a $5 million seed round last October to give the company a total of $21 million raised to date. This latest round was driven by the company’s go-to-market strategy and customer traction after having acquired over 30 customers in 12 countries.
Over the past few quarters, the company began working with Fortune 500 companies, including Accenture and Siemens Energy, across industries like professional services, medical devices and energy, Lee said. As spending on AI skills is expected to exceed $79 billion by 2022, he says Workera will assist in closing the gap.
“We are seeing a need to measure skills,” he added. “The size of the engagements are a sign as is the interest for tech and non-tech teams to develop AI literacy, which is a more pressing need.”
As a result, it was time to increase the engineering and science teams, Katanforoosh said. He plans to use the new funding to invest in more talent in those areas and to build out new products. In addition, there are a lot of natural language processes going on behind the scenes, and he wants the company to better understand it at a granular level so that the company can assess people more precisely.
Carmen Chang, general partner and head of Asia at NEA, said she is a limited partner in Ng’s AI fund and in Coursera, and has looked at a lot of his companies.
She said she is “very excited” to lead the round and about Workera’s concept. The company has a good understanding of the employee skill set, and with the tailored learning program, will be able to grow with company needs, Chang added.
“You can go out and hire anyone, but investing in the people that you have, educating and training them, will give you a look at the totality of your employees,” Chang said. “Workera is able to go in and test with AI and machine learning and map out the skill sets within a company so they will be able to know what they have, and that is valuable, especially in this environment.”
Meet Taktile, a new startup that is working on a machine learning platform for financial services companies. This isn’t the first company that wants to leverage machine learning for financial products. But Taktile wants to differentiate itself from competitors by making it way easier to get started and switch to AI-powered models.
A few years ago, when you could read ‘machine learning’ and ‘artificial intelligence’ in every single pitch deck, some startups chose to focus on the financial industry in particular. It makes sense as banks and insurance companies gather a ton of data and know a lot of information about their customers. They could use that data to train new models and roll out machine learning applications.
New fintech companies put together their own in-house data science team and started working on machine learning for their own products. Companies like Younited Credit and October use predictive risk tools to make better lending decisions. They have developed their own models and they can see that their models work well when they run them on past data.
But what about legacy players in the financial industry? A few startups have worked on products that can be integrated in existing banking infrastructure. You can use artificial intelligence to identify fraudulent transactions, predict creditworthiness, detect fraud in insurance claims, etc.
Some of them have been thriving, such as Shift Technology with a focus on insurance in particular. But a lot of startups build proof-of-concepts and stop there. There’s no meaningful, long-term business contract down the road.
Taktile wants to overcome that obstacle by building a machine learning product that is easy to adopt. It has raised a $4.7 million seed round led by Index Ventures with Y Combinator, firstminute Capital, Plug and Play Ventures and several business angels also participating.
The product works with both off-the-shelf models and customer-built models. Customers can customize those models depending on their needs. Models are deployed and maintained by Taktile’s engine. It can run in a customer’s cloud environment or as a SaaS application.
After that, you can leverage Taktile’s insights using API calls. It works pretty much like integrating any third-party service in your product. The company tried to provide as much transparency as possible with explanations for each automated decision and detailed logs. As for data sources, Taktile supports data warehouses, data lakes as well as ERP and CRM systems.
It’s still early days for the startup, and it’s going to be interesting to see whether Taktile’s vision pans out. But the company has already managed to convince some experienced backers. So let’s keep an eye on them.
Those at risk are always vigilant for the signs of a stroke in progress, but no one can be vigilant when they’re sleeping, meaning thousands of people suffer “wake-up strokes” that are only identified hours after the fact. Zeit Medical’s brain-monitoring wearable could help raise the alarm and get people to the hospital fast enough to mitigate the stroke’s damage and potentially save lives.
A few decades ago, there wasn’t much anyone could do to help a stroke victim. But an effective medication entered use in the ’90s, and a little later a surgical procedure was also pioneered — but both need to be administered within a few hours of the stroke’s onset.
Orestis Vardoulis and Urs Naber started Zeit (“time”) after seeing the resources being put toward reducing the delay between a 911 call regarding a stroke and the victim getting the therapy needed. The company is part of Y Combinator’s Summer 2021 cohort.
“It used to be that you couldn’t do anything, but suddenly it really mattered how fast you got to the hospital,” said Naber. “As soon as the stroke hits you, your brain starts dying, so time is the most crucial thing. People have spent millions shrinking the time between the 911 call and transport, and from the hospital door to treatment. but no one is addressing those hours that happen before the 911 call — so we realized that’s where we need to innovate.”
If only the stroke could be identified before the person even realizes it’s happening, they and others could be alerted and off to the hospital long before an ambulance would normally be called. As it turns out, there’s another situation where this needs to happen: in the OR.
For illustrative purposes, an EEG signal that changes its character can be detected quickly by the algorithm. Image Credits: Zeit
Surgeons and nurses performing operations obviously monitor the patient’s vitals closely and have learned to identify the signs of an impending stroke from the EEG monitoring their brainwaves.
“There are specific patterns that people are trained to catch with their eyes. We learned from the best neurologists out there how they process this data visually, and we built a tool to detect that automatically,” said Vardoulis. “This clinical experience really helped, because they assisted in defining features within the signal that helped us accelerate the process of deciding what is important and what is not.”
The team created a soft, wearable headband with a compact EEG built in that monitors the relevant signals from the brain. This data is sent to a smartphone app for analysis by a machine learning model trained on the aforementioned patterns, and if anything is detected, an alarm is sent to the user and pre-specified caregivers. It can also be set to automatically call 911.
“The vast majority of the data we have analyzed comes out of the OR,” said Vardoulis, where it can immediately be checked against the ground truth. “We saw that we have an algorithm that can robustly capture the onset of events in the OR with zero false positives.”
That should translate well to the home, they say, where there are actually fewer complicating variables. To test that, they’re working with a group of high-risk people who have already had one stroke; the months immediately following a stroke or related event (there are various clinically differentiated categories) is a dangerous one when second events are common.
“Right now we have a research kit that we’re shipping to individuals involved in our studies that has the headband and phone. Users are wearing it every night,” said Vardoulis. “We’re preparing for a path that will allow us to go commercial at some point in 2023. We’re working with he FDA to define the clinical proof needed to get this clear.”
They’ve earned a “Breakthrough Device” classification, which (like stroke rehabilitation company BrainQ) puts them in position to move forward quickly with testing and certification.
“We’re going to start in the U.S., but we see a need globally,” said Naber. “There are countries where aging is even more prevalent and the support structure for disability care is even less.” The device could significantly lower the risk and cost of at-home and disability care for many people who might otherwise have to regularly visit the hospital.
The plan for now is to continue to gather data and partners until they can set up a large-scale study, which will almost certainly be required to move the device from direct-to-consumer to reimbursable (i.e., covered by insurance). And although they are totally focused on strokes for the present, the method could be adapted to watching for other neurological conditions.
“We hope to see a future where everyone with a stroke risk is issued this device,” said Vardoulis. “We really do see this as the missing puzzle piece in the stroke care continuum.”
Bodo.ai, a parallel compute platform for data workloads, is developing a compiler to make Python portable and efficient across multiple hardware platforms. It announced Wednesday a $14 million Series A funding round led by Dell Technologies Capital.
Python is one of the top programming languages used among artificial intelligence and machine learning developers and data scientists, but as Behzad Nasre, co-founder and CEO of Bodo.ai, points out, it is challenging to use when handling large-scale data.
Bodo.ai, headquartered in San Francisco, was founded in 2019 by Nasre and Ehsan Totoni, CTO, to make Python higher performing and production ready. Nasre, who had a long career at Intel before starting Bodo, met Totoni and learned about the project that he was working on to democratize machine learning and enable parallel learning for everyone. Parallelization is the only way to extend Moore’s Law, Nasre told TechCrunch.
Bodo does this via a compiler technology that automates the parallelization so that data and ML developers don’t have to use new libraries, APIs or rewrite Python into other programming languages or graphics processing unit code to achieve scalability. Its technology is being used to make data analytics tools in real time and is being used across industries like financial, telecommunications, retail and manufacturing.
“For the AI revolution to happen, developers have to be able to write code in simple Python, and that high-performance capability will open new doors,” Totoni said. “Right now, they rely on specialists to rewrite them, and that is not efficient.”
Joining Dell in the round were Uncorrelated Ventures, Fusion Fund and Candou Ventures. Including the new funding, Bodo has raised $14 million in total. The company went after Series A dollars after its product had matured and there was good traction with customers, prompting Bodo to want to scale quicker, Nasre said.
Nasre feels Dell Technologies Capital was “uniquely positioned to help us in terms of reserves and the role they play in the enterprise at large, which is to have the most effective salesforce in enterprise.”
Though he was already familiar with Nasre, Daniel Docter, managing director at Dell Technologies, heard about Bodo from a data scientist friend who told Docter that Bodo’s preliminary results “were amazing.”
Much of Dell’s investments are in the early-stage and in deep tech founders that understand the problem. Docter puts Totoni and Nasre in that category.
“Ehsan fits this perfectly, he has super deep technology knowledge and went out specifically to solve the problem,” he added. “Behzad, being from Intel, saw and lived with the problem, especially seeing Hadoop fail and Spark take its place.”
Meanwhile, with the new funding, Nasre intends to triple the size of the team and invest in R&D to build and scale the company. It will also be developing a marketing and sales team.
The company is now shifting from financing to customer- and revenue-focused as it aims to drive up adoption by the Python community.
“Our technology can translate simple code into the fast code that the experts will try,” Totoni said. “I joined Intel Labs to work on the problem, and we think we have the first solution that will democratize machine learning for developers and data scientists. Now, they have to hand over Python code to specialists who rewrite it for tools. Bodo is a new type of compiler technology that democratizes AI.”