Labster, the Denmark headquartered startup building virtual laboratory simulations for STEM students, has raised $21 million in Series B funding.
Leading the round is Owl Ventures, with participation from Balderton Capital, Northzone and Swisscom Ventures. Previous backers Nordic Makers, David Helgason, EduCapital and Entangled Group also followed on, bringing the total raised by the company to date to $35 million.
Launched back in 2013, Labster provides interactive laboratory simulations powered by VR for students that wish to explore lab experiments in biology, chemistry, physics, engineering and general sciences. It offers 70 virtual labs with the aim of increasing participation in STEM curricula, while also improving learning outcomes and retention rates.
“STEM-related careers are increasingly becoming both more in demand and also more important than ever before,” says Labster co-founder Michael Bodekaer. “However, most students will never have access to expensive, high-tech labs, or have enough time in the lab to learn critical skills they’ll need”
Specifically, Labster’s fully interactive virtual lab simulations are designed to engage and stimulate a student’s natural curiosity as they learn. The idea is to provide an environment where can experiment with and explore different lab scenarios — and at less cost than brick ‘n’ mortar labs.
“We aim to provide modern science learning that is cost and time-effective,” says Bodekaer.
More than 150 universities and high schools around the world used Labster’s virtual labs in 2018, a quadrupling of annual growth that put the software in the hands of more than 200,000 students worldwide. Those educational institutions include Harvard, MIT, Stanford, Exeter University and ETH Zurich. Labster has also developed partnerships with industry leaders in technology and education, such as Google and Arizona State University, Lenovo, Pearson and Springer.
Meanwhile, this latest round will be used to accelerate the expansion of Labster’s STEM content catalog and development of new lab simulations. The funding will also enable the company to continue to scale its U.S. operations, including customer support and sales.
“Our main competitor is the status quo i.e. institutions hesitant to adopt new technology even though it’s been proven that virtual labs increase student engagement and achievement,” adds Bodekaer. “There can be several reasons why they are hesitant but the most common one we see is educators not feeling like they have the time or knowledge to implement virtual labs into their teaching. That’s why we are continuously working on our training and on-boarding to help educators get started with virtual labs. Our goal is for educators to feel like we are holding their hand every step of the way and fortunately the feedback we are getting indicates that we are doing a pretty good job of that”.
To that end, Labster is sold as a subscription service to universities and high schools. The edtech company offers two subscription price models: institution accounts and individual student accounts.
Last week, at TechCrunch’s robotics event at UC Berkeley, we sat down with four VCs who are making a range of bets on robotics companies, from drone technologies to robots whose immediate applications aren’t yet clear. Featuring Peter Barrett of Playground Global, Helen Liang of FoundersX Ventures, Eric Migicovsky of Y Combinator and Andy Wheeler of GV (pictured above), we covered a lot of terrain (no pun intended), including whether last-mile delivery robots make sense and how much robots should be expected to do without human intervention.
We also discussed climate change and how it factors into their bets, and why the many private enterprises focused on creating fully automated vehicles may need to do much more to empower the cities in which they plan to operate. You can find excerpts of our talk below. And for access to the full transcript, become a member of Extra Crunch. Learn more and try it for free.
TC: How do you think about investing in the here and now, versus the future (which is complicated for VCs, given that venture funds need to produce returns within a ten-year window, typically):
PB: One of the challenges with investing in robotics is that robotics companies do tend to take a lot longer to mature than your average enterprise SaaS company. There are some classes of investments that we know the technology works; it’s just a question of commercializing it and bringing it to market, and Canvas [a Playground-backed company that makes autonomous warehouse carts and was just acquired by Amazon] did an extraordinary job of finding a market that existed and had technology in hand that would solve that problem.
There’s other stuff like the amazing work that the folks are doing at Agility [Robotics] with a biped that can operate for many hours in unstructured human environments that today is really, candidly, a research robot, and to reach its long-term aspirations, there’s a whole other set of technologies that we’ll need to develop as the company matures.
We think about blending the stuff that’s very impactful but is going to take a long time because it’s fundamentally a new science and technology that needs to be created, [with] immediate applications of technologies that are proven today, that we’re deploying against real markets.
AW: As for whether we try to build a portfolio where there are exits at different stages, generally, when I’m looking to invest in a robotics thing, I understand that the timeframes can be fairly long, and so what we’re looking for are things that really are going to be very large opportunities — that can generate billion-dollar-plus exits.
TC: A growing number of small last-mile delivery robots has attracted funding. Helen, your firm is an investor in one of these startups, Robby. What’s the appeal?
HL: We look at where we see a pain point in the market. During our team meetings on Fridays, we always use DoorDash. It feels awkward when we order a $100 meal, and the delivery person has driven a long way. We’ll give him a $15, but it’s still [tricky for that person] in terms of economics. If you have a central station for the food delivery, and robots can handle that last-mile delivery, we think that’s a more cost-effective approach.
Robby has partnered with PepsiCo [to delivering snacks to students attending the University of the Pacific in Stockton, Ca.] that makes it more like a vending machine, and we think that’s an interesting market, too. We’ll see how fast adoption will happen.
EM: YC is an investor in Robby as well, and we think of this as kind of the perfect example of how hackers can get into a fairly complex industry. When you look at some robotics and specifically autonomous vehicles, you see extremely large investments going into some of the some of the big players, but then at the same time, you see groups and hackers that are able to use off-the-shelf technology to solve real problems that affect businesses or people, and build services or products that that are valuable. We’ve seen this over and over.
You don’t have to be looking for a large VC investment to compete in the space. It is possible to stay frugal stay nimble and build something on a small scale to demonstrate that you found a problem that people are willing to pay money to solve. Then, if you’re interested, [you can] pursue larger VC investment or not. It’s kind of open right now.
TC: VCs we’ve talked with in the past have suggested that in robotics, they often see cool ideas for which there isn’t necessarily a market or big market need. Is this also your experience?
PB: This is a common pattern where there was some mechanism, some capability of the robot, some feat of dexterity or something [and founders think, ‘That’s really cool, I’m going to make a company out of it.’ But we think about it in terms of, what do you want from the robots? What’s the outcome that everybody agrees is worthwhile? And then, how do you find and build companies to achieve those goals?
One thing we’re struggling with right now is that there’s no real hardware or software platforms. You think about 10 years hence [and] the kinds of things we’ll be investing in, [and it’s] robotics applications that are aggregates of neural networks and some explicit software bound together in some form that can be delivered, so a large enterprise can use an application and not have everybody start from first principles. Because right now, when you built a robotics application, you make all the hardware, you make all the software. All the intellectual and actual capital [money] gets dissipated, building and rebuilding those same things. So robotics applications over time will be investable, much more like the way we invest in software, and that will allow smaller units of creativity to produce useful products.
TC: Andy, how long do you think it’s going to take until we get there?
AW: I think I think we’re making we’re making steady progress on that front. To your earlier question, this space has a lot of folks that are building technology a bit in search of a problem. That’s a common thing in startups generally. I would encourage everybody who’s looking to build a startup in the space is to really find a burning business problem. In the course of solving those [problems], people will build these platforms that Peter was talking about, and we’ll eventually get there in terms of [founders] just having to focus on the application layer.
TC: There are so many buckets: delivery robots, self-driving trucks. Both relate in ways to the overarching problem for our age, which is climate change. How much do you factor climate change into the investing decisions that you make?
PB: When we look at applications and robotics in agricultural, a lot of [our questions are] around how do you deal with a minimum carbon footprint, [and] how you replace workers who are missing. And dealing with climate change will be increasingly be a central thought in what we want from our robots. [After all] what we want from them is the ability to maintain or improve the lifestyles we have without further unwinding the environment.
TC: We talked backstage, and you think we are over-indexing on autonomy as the answer.
PB: When we think about autonomy, it’s not clear how autonomy helps cities. . . There are absolutely applications for autonomy, [including] on a farm or in a logistics environment. I think we still really don’t know how to do Level 5 [which is complete automation, requiring zero human assistance]. And I don’t think we know whether it’s exponentially hard or asymptotically. I think it’s decades before there’s any significant Level 5.
[In the meantime, if] we cared about safety, we’d install roundabouts or lower the blood alcohol limit and not try and make a sentient vehicle that drives on the road the way we do, right?
I’d much rather see having the city collaborate with the vehicles and instrument the city to collaborate with clever vehicles for the benefit of everybody who lives there. But that’s not Level 5 autonomy as the way we think of it
EM: It’s slightly interesting that autonomous vehicles, specifically the individual passenger car, evolved in America, because it’s one of the countries that has the least public transport per capita. And that that’s one of the things that the industry has to acknowledge — that there are other options that can be blended into the transport solutions for cities.
It seems like it might be happening because it’s something that an individual can take somewhat control over. You can’t own a bus, but you can own or [rent] a self-driving car.
PB: Or [an electric] scooter or a bike, right. The future of mobility is going to be a blending of all of these things. But not taking advantage of a logistics platform in a city means you’re kind of doing it the hard way, trying to make a robot to have all the human priors required to drive safely. And it’s just not clear that we know how to do that yet.
TC: Andy, GV is a big investor in Uber. What what’s your thinking? Does the city need to be a kind of central brain in order for these private enterprises to work effectively?
AW: I don’t think it’s a strict requirement at all. We’ve seen success with with self-driving trials where the city is not super involved from an infrastructure perspective, I do think it makes it a lot easier if that’s the case, though.
Vue.ai, a U.S/India startup that develops an AI platform to help online retailers work more efficiently and sell more, has announced a $17 million Series B round.
The investment is led by Falcon Edge Capital with participation from Japan’s Global Brain and existing backer Sequoia Capital India. Parent company Mad Street Den was founded in 2014 and it raised $1.5 million a year later, Sequoia then bought into the business via an undisclosed deal in 2016. Vue.ai is described as an “AI brand” from Mad Street Den and, all combined, the two entities have now raised $27 million from investors.
In an interview with TechCrunch, Vue.ai CEO and co-founder Ashwini Asokan — who started Mad Street Den with her husband Anand Chandrasekaran — explained that Vue.ai is a “retail vertical” of Mad Street Den that launched in 2016, she said that the company may add “another vertical in a year or two.”
Vue.ai is solely focused on working with online retailers, predominantly in the fashion space, and it does so in a number of ways. That includes expected areas such as automating product tagging and personalized recommendations (based on that tag library), as well as visual search using photos as input and tailored product discovery.
Areas that Vue.ai also plays in which surprised me, at least, include generating human models who wear clothing items — thus saving considerable time, money and effort on photo shoots — and an AI stylist that doesn’t take human form but does learn a user’s style and help them outfit themselves accordingly.
Tagging and visuals may appear boring, but these are hugely important areas for retailers who have huge amounts of SKUs, items for sale, on their site. Making sure the right person finds the right item is critical to making a sale, and Vue.ai’s goal is to automate as much of that heavy-lifting as possible. Even tagging is essential because it needs to be done consistently if it is to work properly.
Ashwini Asokan, CEO and Founder of Vue.ai
More than just working correctly, Vue.ai aims to help online retailers, who often run a tight ship in terms of profitability, save money and get new product online and in front of consumer eyeballs quickly.
“These are solutions that optimize the bottom line for retail companies,” said Asokan, who spent over a decade working in the U.S before returning home in India in 2015. “We are digitizing products 10X faster than you did before… you cannot afford to lose productivity and efficiency, online retail is not somewhere you can lose money.”
“We want to be that data brain mapping digital products,” she added.
Vue.ai is now pushing into new areas, which include advertising and development of videos and marketing content.
“The future of retail is entertainment and the experience economy is the small start of that era,” Asokan said, reflecting on the trend of social media buying through platforms like Instagram and the rise of live-streaming e-commerce in China.
“The electricity that powers all of these complicated retail interactions is content; we need to understand content and every customer style profile and merchandise,” she added.
Some of Vue.ai’s public customers include Macy’s and Diesel in the U.S, Latin American e-commerce firm Mercadolibre and Indian conglomerate Tata .
Vue.ai is headquartered in Redwood City with an office in Chennai, India. Asokan said it is planning to expand that presence with new locations in Seattle, for tech hires, and Japan and Spain to help provide closer support for customers. The company doesn’t disclose raw numbers, but it said that annual revenue grew by four hundred percent in 2018, which was its third year since incorporation.
Holded, the Barcelona-based startup that offers a SaaS to help SMEs with a range of business tasks, has raised €6 million in Series A funding. The round is led by Lakestar, with previous backers Nauta Capital and Seedrocket 4Founders Capital following on.
Founded in 2016 by Bernat Ripoll and Javi Fondevila, Holded describes itself as a “Business Operating System”. The idea is to provide a single platform for small to medium-sized business owners to manage every aspect of their business.
The Saas covers financial management such as accounting and invoicing to HR, CRM, and project and inventory management. In addition, the customisable platform offers multiple integrations to connect with a number of popular payment and e-commerce solutions. They include Amazon, Paypal and Shopify.
Alongside this, Holded is able to “automate” a number of core business administration tasks via the cloud-based platform’s own AI. It also uses data garnered through the use of the software to benchmark business performance and provide managers and business owners with actionable insights with regards to how they might increase sales, reduce expenses and save time.
Holded co-founder Bernat Ripoll says the company set out to develop next generation Enterprise-Resource-Planning (ERP) software that addresses the needs of modern companies, which is something that appears to be resonating with SMEs. Since closing its seed round in early 2018, Holded has increased user numbers from 10,000 to 30,000, claiming to now be the leader in Spain.
Meanwhile, Holded says the new capital will be used to accelerate its expansion into international markets. The Spanish startup will also invest further in the development of the software’s core functionality.
“[We] now aim to replicate this [success] in other countries while continuing to consolidate the Spanish market,” says Holded co-founder Javi Fondevila, adding that the startup plans to roll out new product features and “country-specific” integrations.
SalesWhale, a Singapore-based startup that uses AI to help marketers and salespeople generate leads, has announced a Series A round worth $5.3 million.
The investment is led by Monk’s Hill Ventures — the Southeast Asia-focused firm that led SalesWhale’s seed round in 2017 — with participation from existing backers GREE Ventures, Wavemaker Partners, and Y Combinator. That’s right, SalesWhale is one a select few Southeast Asian startups to have been through YC, it graduated back in summer 2016.
SalesWhale — which calls itself “a conversational email marketing platform” — uses AI-powered ‘bots’ to handle email. In this case, its digital workforce is trained for sales leads. That means both covering the menial parts of arranging meetings and coordination, and the more proactive side of engaging old and new leads.
Back when we last wrote about the startup in 2017, it had just half a dozen staff. Fast forward two years, and that number has grown to 28, CEO Gabriel Lim explained in an interview. The company is going after more growth with this Series A money, and Lim expects headcount to jump past 70 while SalesWhale is deliberating opening an office in California. That location would be primarily to encourage new business and increase communication and support for existing clients, most of whom are located in the U.S, according to Lim. Other hires will be tasked with increasing integration with third-party platforms, and particularly sales and enterprise services.
The past two years have also seen SalesWhale switch gears and go from targeting startups as customers, to working with mid-market and enterprise firms. SalesWhale’s “hundreds” of customers include recruiter Randstad, educational company General Assembly, and enterprise service business Unit4. As it has added greater complexity to its service, so the income has jumped from an initial $39-$99 per seat all those years ago to over $1,000 per month for enterprise customers.
SalesWhale’s founding team (left to right): Venus Wong, Ethan Lee and Gabriel Lim
While AI is a (genuine) threat to many human jobs, SalesWhale sits on the opposite side of that problem in that it actually helps human employees get more work done. That’s to say that SalesWhale’s service can get stuck into a pile (or spreadsheet) of leads that human staff don’t have time for, begin reaching out, qualifying leads and sending them on to living and breathing colleagues to take forward.
“A lot of potential leads aren’t touched” by existing human teams, Lim reflected.
But when SalesWhale reps do get involved, they are often not recognized as the bots they are.
“Customers are often so convinced they are chatting with a human — who is sending collateral, PDFs and arranging meetings — that they’ll say things like ‘I’d love to come by and visit someday,’” Lim joked in an interview.
“Indeed, a lot of times, sales team refer to [SalesWale-powered] sales assistant like they are a real human colleague,” he added.
The round is led by Japan’s SBI Investment with participation from sibling fund SBI Ven Capital and another Japanese investor Beenext. Existing Mfine backers Stellaris Venture Partners and Prime Venture Partners also returned to follow on. Mfine has now raised nearly $23 million to date.
“In India, at a macro-level, good doctors are far and few and distributed very unevenly,” Kompalli said in an interview with TechCrunch. “We asked ‘Can we build a platform that is a very large hospital on the cloud?’, that’s the fundamental premise.”
There’s already plenty of money in Indian health tech platforms — Practo, for one, has raised over $180 million from investors like Tencent — but Mfine differentiates itself with a focus on partnerships with hospitals and clinics, while others have offered more daily health communities that include remote sessions with doctors and healthcare professionals who are recruited independently of their day job.
“We are entering a different phase of what is called health tech… the problems that are going to be solved will be much deeper in nature,” Kompalli said in an interview with TechCrunch.
Mfine makes its money as a digital extension of its healthcare partners, essentially. That means it takes a cut of spending from consumers. The company claims to work with over 500 doctors from 100 ‘top’ hospitals, while there’s a big focus on tech. In particular, it says that an AI-powered ‘virtual doctor’ can help in areas that include summarising diagnostic reports, narrowing down symptoms, providing care advice and helping with preventative care. There are also other services, including medicine delivery from partner pharmacies.
To date, Mfine said that its platform has helped with over 100,000 consultations across 800 towns in India during the last 15 months. It claims it is seeing around 20,000 consultations per month. Beyond helping increase the utilization of GPs — Mfine claims it can boost their productivity 3/4X — the service can also help hospitals and centers increase their revenue, a precious commodity for many.
Going forward, Kompalli said that the company is increasing its efforts with corporate companies, where it can help cover employee healthcare needs, and developing its insurance-style subscription service. Over the coming few years, that channel should account for around half of all revenue, he added.
A more immediate goal is to expand its offline work beyond Hyderabad and Bangalore, the two cities where it currently is.
“This round is a real endorsement from global investors that the model is working,” he added.
Blueshift is startup founded by tech industry veterans, who saw first-hand how difficult cross-channel marketing was. They decided to launch a company and build a cross-channel marketing platform from the ground up that uses AI and machine learning to make sense of the growing amount of customer data. Today, the startup announced a $15 million Series B round to keep it going.
The round was led by Softbank Ventures Asia, a fund focused on AI startups like Blueshift . Previous investors Storm Ventures and Nexus Venture Partners also participated. Today’s investment brings the total raised to $30 million, according the company.
Company co-founder and CEO Vijay Chittoor says the marketing landscape is changing, and he believes that requires a new approach to allow marketers to take advantage of the multiple channels where they could be engaging with customers from a single tool.
“If you thought about the world of customer engagement at Walmart or Groupon [or any other retailer] 10 years ago, it was primarily an email problem. Today, we as customers, we’re interacting with these brands on not just email, but also on mobile notifications, Facebook custom audiences and WeChat [and across multiple other channels],” he explained.
He says that this has created a lot more data, which it turns out is a double-edged sword for marketing pros. “I think on one end, it’s exciting for a marketer or a CMO to have more data and more channels. It gives them more ways to connect. But at the same time, it’s also more challenging because now you have to make sense of thousand times more data. And you have to use it intelligently on not just one channel like email, but you’re now trying to make sense of data across 15 different channels,” Chittoor said.
This a crowded field with big players like Adobe, Salesforce and Oracle, among others, offering similar cross-channel, AI-fueled solution. In addition startups are attracting huge chunks of money to attack this problem, including Klayvio pulling in $150 million a couple of weeks ago and Iterable, which landed $50 million last month.
He says his company’s differentiator is the AI piece, and it is this piece that the company’s lead investor in this round has been focusing on in its investments. The company plans to use this round to continue building out its marketing platform and show marketers how to communicate intelligently across channels wherever the consumer happens to be. Customers include LendingTree, Udacity and BBC.
With remote working becoming more of a norm than ever before, remote interviews have, in turn, become a necessity. But how can you truly assess someone from these? In addition, it’s easy to miss great candidates just because you don’t have time to interview all the candidates.
A number of startups have appeared to try and address the problem. HireVue,
which has raised $93M, has tried to address with an AI-driven ‘Hiring Intelligence’ platform. AllyO, which has raised $19M, is trying to make hiring more efficient by addressing the traditional inefficiencies of lost applicants and conversions due to poor candidate experience. And Arya is a seed stage start-up which uses machine learning to identify successful sourcing patterns and draws potential candidates out of online profiles.
Another player is applying algorithms to the hiring process.
VCV.AI, has now raised $1.7 million to automatically screens job candidates using facial and voice recognition. Yes, it looks like another episode of Black Mirror is on its way…
The investment comes from Japanese VC Will Group, Talent Equity Ventures, 500 Startups and angel investors, including Masahiro Takeshima of Indeed. The funding will help VCV continue to develop its technology and strengthen its position, and will also see it opening an office in Tokyo, Japan.
VCV claims it can help eliminate human bias from the hiring process with preliminarily screening of candidates, automated screening calls, and by conducting these robo-video interviews with voice recognition and video recording.
Through VCV, potential candidates can record a video using a computer or smartphone on iOS or Android. This functions like a real interview, as candidates don’t have the ability to prepare for the questions in advance. Additionally, facial and voice recognition identifies a candidates’ nervousness, mood, and behavior patterns to help recruiters assess whether a person is a good cultural fit for the company.
VCV says this doesn’t replace the job of a recruiter but enhances their toolset so they can find and screen a greater number of candidates more efficiently. The startup says this AI-led approach helps companies save over 20 hours of work with recruiting bots working 24/7 to find, chat, and interview potential candidates.
Clients already include PWC, L’Oreal, Danone, Mars, Schlumberger, and Citibank .
Arik Akverdian, founder and CEO of VCV.AI, said: “AI can improve and streamline the hiring process, while also helping to remove corrosive biases that all humans have. There’s no reason technological innovation shouldn’t transform this area of business—especially considering human talent is an organization’s most important asset.”
We will see how those biases play out once all our hiring is via AI…