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Wright tests its 2-megawatt electric engines for passenger planes
Just like the automotive industry, aerospace has its sights set on going electric — but flying with battery-powered engines is a tougher proposition than rolling. Wright is among the startups looking to change the math and make electrified flight possible at scales beyond small aircraft — and its 2-megawatt engine could power the first generation of large-scale electric passenger planes.
Electric cars have proven to be a huge success, but they have an advantage over planes in that they don’t need to produce enough lift to keep their own mass in the air. Electric planes have been held back by this fundamental conundrum, that the weight of the batteries needed to fly any distance with passengers aboard means the plane is too heavy to fly in the first place.
In order to escape this conundrum, the main thing to improve is efficiency: how much thrust can be produced per watt of power. Since reducing the mass of batteries is a long, slow process, it’s better to innovate in other ways: materials, airframe and of course the engine, which in traditional jets is a huge, immensely heavy and complex internal combustion one.
Electric engines are generally lighter, simpler and more reliable than fuel-powered ones, but in order to achieve flight you need to reach a certain level of efficiency. After all, if a jet burned a thousand gallons of fuel per second, the plane couldn’t hold the amount needed to take off. So it falls to companies like Wright and H3x to build electric engines that can produce more thrust from the same amount of stored energy.
While H3x is focused on small aircraft that will probably be taking flight sooner, Wright founder Jeff Engler explained that if you want to take on aerospace’s carbon footprint, you really have to start looking at commercial passenger jets — and Wright is planning to make one. Fortunately, despite the company’s name, they don’t need to build it entirely from scratch.
“We’re not reinventing the concept of the wing, or the fuselage, or anything like that. What changes is what propels the aircraft forward,” said Engler. He likened it to electric vehicles in that much of the car doesn’t change when you go electric, mainly the parts that have operated the same way in principle for a century. All the same, integrating a new propulsion system into a plane isn’t trivial.
Wright’s engine is a 2-megawatt motor that produces the equivalent of 2,700 horsepower, at an efficiency of around 10 kilowatts per kilogram. “It’s the most powerful motor designed for the electric aerospace industry by a factor of 2, and it’s substantially lighter than anything out there,” said Engler.
The lightness comes from a ground-up redesign using a permanent magnet approach with “an aggressive thermal strategy,” he explained. A higher voltage than is normally employed for aerospace purposes and an insulation system to match enable an engine that hits the power and efficiency levels required to put a large plane in flight.
Image Credits: Wright
Wright is making sure its engines can be used by retrofitted aircraft, but it’s also working on a plane of its own with established airframe makers. This first craft would be a hybrid electric, combining the lightweight, efficient propulsion stack with the range of a liquid fuel engine. Relying on hydrogen complicates things but it makes for a much faster transition to electric flight and a huge reduction in emissions and fuel use.
Several of Wright’s motors would be attached to each wing of the proposed aircraft, providing at least two benefits. First, redundancy. Planes with two huge engines are designed to be capable of flying even if one fails. If you have six or eight engines, one failing isn’t nearly so catastrophic, and as a consequence the plane doesn’t need to carry twice as much engine as you need. Second is the stability and noise reduction that comes from having multiple engines that can be adjusted individually or in concert to reduce vibration and counteract turbulence.
Right now the motor is in lab testing at sea level, and once it passes those tests (some time next year is the plan) it will be run in an altitude simulation chamber and then up at 40,000 feet for real. This is a long-term project, but an entire industry doesn’t change overnight.
Engler was emphatic about the enthusiasm and support the company has received from the likes of NASA and the military, both of which have provided considerable cash, material and expertise. When I brought up the idea that the company’s engine might end up in a new bombing drone, he said he was sensitive to that possibility, but that what he’s seen (and is aiming for) is much more in line with the defense department’s endless cargo and personnel flights. The military is a huge polluter, it turns out, and they want to change that — and cut down on how much money they spend on fuel every year as well.
“Think of how things changed when we went from propellers to jets,” said Engler. “It redefined how an airplane operates. This new propulsion tech allows for reshaping the entire industry.”
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Performance marketing agency MuteSix bets on content and data to boost DTC e-commerce
Warby Parker filing to IPO last week was one more sign that direct-to-consumer (DTC) is an extremely powerful e-commerce trend. But LA-based performance marketing agency MuteSix didn’t wait that long to build its business around scaling DTC brands.
Created in 2014 and acquired by Dentsu in 2019, MuteSix was recommended to TechCrunch by Rhoda Ullmann, VP Consumer at Sense, a Boston-based startup building a home energy monitor. “They demonstrate best-in-class expertise with Facebook and Google paid ad platforms. They also have a very smart and efficient approach to creative development that was critical to helping us scale,” she wrote. (If you have growth marketing agencies or freelancers to recommend, please fill out our survey!)
Besides Sense, MuteSix’s former and current clients include companies such as Adidas, Petco, Ring and Theragun, to whom it provides a full range of marketing services, including top-notch direct response videos. But regardless of whether you can afford this, we think you’ll learn interesting lessons from our conversation with their CRO, Greg Gillman. The key takeaway? In today’s highly competitive ad environment, both content and data are kings.
Editor’s note: The interview below has been edited for length and clarity.
What can you tell us about MuteSix as an agency?
Image Credits: MuteSix
Greg Gillman: We’ve been around for about nine years. We started out as a Facebook ad agency — as opposed to a lot of agencies that start out by saying they do everything, we decided to focus on what we were really good at. At the time, it was doing Facebook media buying for e-commerce companies. Primarily here in LA, which is kind of the hub of these companies, but also all over. And then bit by bit, we grew the organization.
At this point, we’re a little over 400 people, and we manage upward of $500 million in spend on Facebook and Google, including Instagram and YouTube. What we’ve grown into is a one-stop shop for DTC e-commerce companies: We manage all the channels that a DTC brand needs. And we’re a performance agency; everything we do is based on results. People come to us to drive revenue into their e-commerce businesses.
Why do you think that performance marketing is the right fit for DTC?
DTC entrepreneurs are more focused on immediate impact, because if they’re not selling product, there’s no large brand propping them up. So I think that doing DTC marketing requires you to be more performance focused. For agencies that work with large brands, usually it’s more about impression buying versus performance buying. They can say: I did a reach campaign today to hit 10 million eyeballs, and whatever happens happens, because at the end of the day, you just told us to do 10 million impressions. It’s different than working with a group like us that’s trying to optimize every small piece of the funnel, and being accountable for the entire funnel to drive as much sales or revenue.
What type of clients do you work with?
The majority of the companies we work with are digitally native DTC companies. We’ve mostly stayed in that lane, because we’re really good at it. That being said, we work with companies of all sizes — startups, companies that are already established, and very large companies that need to rework both their creative and their media buying strategy.
I oversee sales, marketing and partnerships, and my role is really trying to figure out which brands make most sense to partner with MuteSix. We’re looking for high-growth brands that we can scale, and we’ve learned through the years that what works well are demonstrable products that have cool user value props.
We’ve worked with lots of startups at different points in the funnel, starting from the ground up and working with them through various rounds of funding, all the way through acquisitions, including two by unicorns. But these days, ground up is tougher. I like them to have some proof of concept — putting through $10,000-$15,000 per month on Facebook or $5,000-10,000 on Google usually shows me that there’s some life to it. But I don’t want to limit us if it’s a cool idea. I talk to a lot of people who come back once they’ve proven it out a little bit.
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What kind of clients are definitely not a good fit?
It won’t be a fit if there’s no real unique value prop for the product. If it’s just another run-of-the-mill company, a consultant can charge them a lower amount of money and set up Facebook ads, but what we are looking for are high-growth businesses.
The compensation for our campaign managers is actually tied to the performance of the campaigns, so if I bring a bunch of campaigns that we can’t scale, we’re gonna have a lot of unhappy media buyers who ask: “Greg, why would we take on this brand?” It’s a business model that has helped us attract top talent, but we need to make sure that we’re bringing brands that we think we can scale.
And it’s easier than ever to start a company, but it’s tougher now to scale it and take it past the $2 million-$3 million run rate. So I always revert back to asking founders: What are five reasons why people want to buy your product? What are the five reasons that they don’t? If the entrepreneur has trouble answering this, it’s not going to work. If they can’t tell somebody why their business is good, then we’re not going to be good at selling it.
How is MuteSix different from other agencies?
I’d say the main difference is that we have a 70-person in-house video creative team; and what we’re really good at doing is shooting and coming up with performance content. Not just content that looks and feels great, but video that is reverse-engineered to sell product.
Another key component is that we have a whole data science team that is also integrated with our media buying team, and that helps companies navigate things like attribution and signal loss due to the iOS 14 update. Right now, that means focusing on looking at the whole picture rather than by channel and working on mix-modeling attribution.
What are some of the things your data team focuses on?
One of the biggest things that brands struggle with is figuring out attribution, and how you continue to spend money even though you may have lost some signal into the platform. If Facebook skews too heavily, and Google is on last click, then sometimes it looks like things are never working. To help companies make informed business decisions, we are building statistical models that show information at higher-than-the-platform level.
We are also building better segments of customer profiles that help the clients understand who their core audience is, but also helps us build predictive audiences for finding new people.
Another big thing we’re trying to solve is incrementality. We work with large brands that have a strong organic following on social media; and their question is: “Hey, Greg, why should I spend more money if I would have acquired those users anyway?” So we’ve done incrementality testing with brands that spend a lot in other channels than Facebook and Google. We helped them build out different ways to look at the data so that we continue to spend in those channels and they actually know the incremental lift that they’re getting.
There’s one other piece that I think is super important and usually overlooked: first-party data. We work with brands to try and acquire as much of that first-party data as possible, segment it and use it, because that’s what they’d be left with if Facebook shut off tomorrow.
How do you prepare and adapt for changes in the marketing ecosystem?
Because we work with so many brands, we have a lot of senior leadership on each channel level. We routinely meet across departments and share insights. The data science team also builds pretty robust reporting. We try to stay ahead of our brands and to be forward-thinking about anything that is ultimately going to impact the agency. We’re constantly trying to hack our way through things like the types of content that work and things that we know will help us scale.
That’s how we have always approached it. Every major shift in our business was done to answer the needs of the brands that we were working with. For instance, there’s a data side to our business because it’s more important than ever to use that. Facebook used to be a platform where you could throw anything at the wall, and you would get a 4x or 5x return. No one’s asking about data when you’re literally printing money out of Facebook, right? It only happens when the margins get tight. But then Facebook became a more crowded platform, and the same happened with Google: more advertisers, higher CPM and a more competitive environment. We needed to be smarter about what we were doing, so we built out our data team.
Now there’s two levers that we can pull: the data side and the creative side of the business. Again, we are a performance marketing agency, focusing on all the levers. Because platforms like Facebook are only going to be more competitive, they’re only going to get more expensive, and we are only going to lose more traffic. So the more agile agencies have to think much farther outside of what we are doing on these platforms; because we’re going to make up the incremental revenue on things like SMS, influencer marketing and organic content, to continue to drive money into the top of the funnel.
Why is your content arm so important as a lever?
We have an integrated solution where our media buyers are paired directly with our video editors and producers to allow us to be agile and quick; because as everyone knows, content is king. What we try to do is optimize around things like what we call the thumbs-up rate on Facebook — three-second video views. If I held someone for that long in their newsfeed, I can potentially get them into our flow. We do the same on YouTube, and we do things like this on programmatic, because the name of the game is to get people into the funnel and work them through it. And we’re using both our data science team and our creative team to build out and optimize on the front end around these quick metrics to get things moving.
In my opinion, there’s no close second to an SMB agency that has a content arm like we do. Leveraging our content team to build performance content is one of the biggest levers that we have. Three and a half years ago, Facebook was telling us: “If you don’t build video content, and if you don’t prioritize video in the newsfeed, it’s not going to work.” At the time, we leaned in very hard — and the pain of growing a creative team of 70 people is real, especially in LA. But it’s allowed us to scale our agency.
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Virtual meeting platform Vowel raises $13.5M, aims to cure meeting fatigue
Meetings are an inevitable part of the work day, but as workplaces became more distributed over the past 18 months, Vowel CEO Andy Berman says we are steadily moving toward “death by meeting.”
His virtual meeting platform is the latest to receive venture capital funding — $13.5 million — with the goal of making meetings more useful before, during and after.
Vowel is launching a meeting operating system with tools like real-time transcription; integrated agendas, notes and action items; meeting analytics; and searchable, on-demand recordings of meetings. The company has a freemium business model and will also be rolling out a business plan this fall for $16 per user per month. Extra features will include advanced integrations, security and admin controls.
The Series A was led by David Hornik of Lobby Capital, who was joined by existing investors Amity Ventures and Box Group and a group of individual investors, including Calendly CEO Tope Awotona, Intercom co-founder Des Traynor, Slack VP Ethan Eismann, former Yammer executive Viviana Faga, former InVision president David Fraga and Okta co-founder Frederic Kerrest.
Prior to starting Vowel, Berman was one of the founders of baby monitor company Nanit. The company had teams spread out around the world, and communication was tough as a result. In 2018, the company went looking for a tool that would work for synchronous and asynchronous meetings, but there were still a lot of time zones to manage, he said.
Taking a cue from Nanit’s own baby monitors that were streaming video over 17 hours a day, the idea for Vowel was born, and the company began to focus on the hypothesis that distributed work would be prevalent.
“People initially thought we were crazy, but then the pandemic hit, and everyone was learning how to work remotely,” Berman told TechCrunch. “As we now go back to hybrid work, we see this as an opportunity.”
In 2017, Harvard Business Review reported that executives spent 23 hours in meetings each week. Berman now estimates that the average worker spends half of their time each week in meetings.
Vowel is out to bring Slack, Figma and GitHub components to meetings by recording audio and video that can be paused at any time. Users can add notes and see where those notes fall within a real-time transcription that enables people who arrive late or could not make the meeting to catch up easily. After meetings are over, they can be shared, and Vowel has a search function so that users can go back and see where a particular person or topic was discussed.
The new funding will enable the company to grow its team in product, design and engineering. Vowel plans to hire up to 30 new people over the next year. The company recently closed its beta test and has amassed a 10,000-person waitlist. The public launch will happen in the fall, Berman said.
Workplace productivity and office communication tools are not new concepts, but as Berman explained, became increasingly important when homes became offices over the past 18 months.
Competitors took different approaches to solving these problems: focusing on video conferencing or audio or meeting management with plugins. Berman says an area where many have not succeeded yet is integrating meetings into the typical workflow. That’s where Vowel comes in with its “meeting OS,” he added.
“Our goal is to make meetings more inclusive and worthwhile, which includes the prep, the meeting and the follow-up,” Berman said. “We see the future will be about knowledge management, so the difference between what we are doing is ensuring you can catch up quickly and keep that knowledge base. A Garner report said that 75% of workplace meetings will be recorded by 2025, and that is a trend we are reinventing from the ground up.”
David Hornik, founding partner at Lobby Capital, said he became acquainted with Vowel from its existing investor Amity Ventures. Hornik, who sits on the GitLab board, said GitLab was one of the largest distributed companies in the tech space, prior to the pandemic, and saw first-hand the challenge of making distributed teams functionable.
When Hornik heard about Vowel, he said he “jumped quickly” on the opportunity. His firm typically invests in platform businesses that have the capacity to transform business spaces. Many are pure software, like Splunk or GitLab, while others are akin to Bill.com, which transformed how small businesses manage financial operations, he added.
All of those combine into a company, like Vowel, especially given the company’s vision for a meeting OS to transform a meeting space that hadn’t moved forward in decades, he said.
“This was quickly obvious to me because my day is meetings — an eight-Zoom day is a normal day — I just wish I could remember everything,” Hornik said. “Speaking with early customers using the product, when I asked them what they would do if this ever went away, the first thing they said was ‘cry,’ and, because there was no alternative, would return to Zoom or other tools, but it would be a big setback.”
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Seqera Labs grabs $5.5M to help sequence COVID-19 variants and other complex data problems
Bringing order and understanding to unstructured information located across disparate silos has been one of the more significant breakthroughs of the big data era, and today a European startup that has built a platform to help with this challenge specifically in the area of life sciences — and has, notably, been used by labs to sequence and so far identify two major COVID-19 variants — is announcing some funding to continue building out its tools to a wider set of use cases, and to expand into North America.
Seqera Labs, a Barcelona-based data orchestration and workflow platform tailored to help scientists and engineers order and gain insights from cloud-based genomic data troves, as well as to tackle other life science applications that involve harnessing complex data from multiple locations, has raised $5.5 million in seed funding.
Talis Capital and Speedinvest co-led this round, with participation also from previous backer BoxOne Ventures and a grant from the Chan Zuckerberg Initiative, Mark Zuckerberg and Dr. Priscilla Chan’s effort to back open source software projects for science applications.
Seqera — a portmanteau of “sequence” and “era”, the age of sequencing data, basically — had previously raised less than $1 million, and quietly, it is already generating revenues, with five of the world’s biggest pharmaceutical companies part of its customer base, alongside biotech and other life sciences customers.
Seqera was spun out of the Centre for Genomic Regulation, a biomedical research center based out of Barcelona, where it was built as the commercial application of Nextflow, open source workflow and data orchestration software originally created by the founders of Seqera, Evan Floden and Paolo Di Tommaso, at the CGR.
Floden, Seqera’s CEO, told TechCrunch that he and Di Tommaso were motivated to create Seqera in 2018 after seeing Nextflow gain a lot of traction in the life science community, and subsequently getting a lot of repeat requests for further customization and features. Both Nextflow and Seqera have seen a lot of usage: the Nextflow runtime has been downloaded more than 2 million times, the company said, while Seqera’s commercial cloud offering has now processed more than 5 billion tasks.
The COVID-19 pandemic is a classic example of the acute challenge that Seqera (and by association Nextflow) aims to address in the scientific community. With COVID-19 outbreaks happening globally, each time a test for COVID-19 is processed in a lab, live genetic samples of the virus get collected. Taken together, these millions of tests represent a goldmine of information about the coronavirus and how it is mutating, and when and where it is doing so. For a new virus about which so little is understood and that is still persisting, that’s invaluable data.
So the problem is not if the data exists for better insights (it does); it is that it’s nearly impossible to use more legacy tools to view that data as a holistic body. It’s in too many places, and there is just too much of it, and it’s growing every day (and changing every day), which means that traditional approaches of porting data to a centralized location to run analytics on it just wouldn’t be efficient, and would cost a fortune to execute.
That is where Segera comes in. The company’s technology treats each source of data across different clouds as a salient pipeline which can be merged and analyzed as a single body, without that data ever leaving the boundaries of the infrastructure where it already exists. Customised to focus on genomic troves, scientists can then query that information for more insights. Seqera was central to the discovery of both the Alpha and Delta variants of the virus, and work is still ongoing as COVID-19 continues to hammer the globe.
Seqera is being used in other kinds of medical applications, such as in the realm of so-called “precision medicine.” This is emerging as a very big opportunity in complex fields like oncology: cancer mutates and behaves differently depending on many factors, including genetic differences of the patients themselves, which means that treatments are less effective if they are “one size fits all.”
Increasingly, we are seeing approaches that leverage machine learning and big data analytics to better understand individual cancers and how they develop for different populations, to subsequently create more personalized treatments, and Seqera comes into play as a way to sequence that kind of data.
This also highlights something else notable about the Seqera platform: it is used directly by the people who are analyzing the data — that is, the researchers and scientists themselves, without data specialists necessarily needing to get involved. This was a practical priority for the company, Floden told me, but nonetheless, it’s an interesting detail of how the platform is inadvertently part of that bigger trend of “no-code/low-code” software, designed to make highly technical processes usable by non-technical people.
It’s both the existing opportunity and how Seqera might be applied in the future across other kinds of data that lives in the cloud that makes it an interesting company, and it seems an interesting investment, too.
“Advancements in machine learning, and the proliferation of volumes and types of data, are leading to increasingly more applications of computer science in life sciences and biology,” said Kirill Tasilov, principal at Talis Capital, in a statement. “While this is incredibly exciting from a humanity perspective, it’s also skyrocketing the cost of experiments to sometimes millions of dollars per project as they become computer-heavy and complex to run. Nextflow is already a ubiquitous solution in this space and Seqera is driving those capabilities at an enterprise level – and in doing so, is bringing the entire life sciences industry into the modern age. We’re thrilled to be a part of Seqera’s journey.”
“With the explosion of biological data from cheap, commercial DNA sequencing, there is a pressing need to analyse increasingly growing and complex quantities of data,” added Arnaud Bakker, principal at Speedinvest. “Seqera’s open and cloud-first framework provides an advanced tooling kit allowing organisations to scale complex deployments of data analysis and enable data-driven life sciences solutions.”
Although medicine and life sciences are perhaps Seqera’s most obvious and timely applications today, the framework originally designed for genetics and biology can be applied to any a number of other areas: AI training, image analysis and astronomy are three early use cases, Floden said. Astronomy is perhaps very apt, since it seems that the sky is the limit.
“We think we are in the century of biology,” Floden said. “It’s the center of activity and it’s becoming data-centric, and we are here to build services around that.”
Seqera is not disclosing its valuation with this round.
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Portcast gets $3.2M to create more transparent and sustainable supply chains
Portcast founders Dr. Lingxiao Xia and Nidhi Gupta
For many manufacturers and freight forwarders, managing logistics is still a very manual process: tracking shipments with a call or online lookup, and entering that data into an Excel spreadsheet. Portcast, which describes itself as a “next-generation logistics operating system,” makes the process more efficient by gathering data from myriad sources and not only track shipments in real-time, but also predicts what might affect its progress, like major weather events, the tide and pandemic-related issues.
The company announced today it has raised $3.2 million in pre-Series A funding, led by Newtown Partners, through the Imperial Venture Fund, with participation from Wavemaker Partners, TMV, Innoport and returning investor SGInnovate. Based in Singapore, Portcast serves clients in Asia and Europe, and will use part of its funding to expand into more markets.
Co-founders Nidhi Gupta and Dr. Lingxiao Xia met at Entrepreneur First in Singapore. Before launching Portcast, Gupta, its chief executive officer, served in leadership roles across Asia at DHL. During that time, she realized the logistic sector’s “inefficiencies are actually an opportunity in this space to create something.” Dr. Xia, who holds a PhD in machine learning and has a background in product development and cloud computing, “was a great complementary fit” and is now Portcast’s chief technology officer.
Portcast says it tracks more than 90% of world trade volume that travels by ocean carriers, and 35% of air cargo, and can forecast demand for 30,000 trade routes. Sources include geospatial data, like satellite data about where ships are, what speed and direction they’re moving in, what ports they are headed for, wind speed and wave height. Portcast also looks at economic patterns (for example, Brexit’s impact on ports around the United Kingdom, and how vaccine rollouts around the world changes airline and ship capacity), weather events like typhoon and disruptions like the Suez Canal blockage.
Other data sources include proprietary transactional data from customers including large shipping companies and freight forwarders.
“The challenge for us is how do we let all of this data speak the same language,” Gupta told TechCrunch. “This data is coming in at different frequencies, different granularities, so how do you consolidate that and make sure the machine can start understanding it and interpreting it.”
Portcast’s two main solutions are currentlu Intelligent Container Visibility for real-time tracking of shipment containers, and Forecasting and Demand Management, which tracks booking patterns. Portcast doesn’t use IoT to track containers since it is cost-prohibitive to place a device in every one, but is working with IoT providers on hybrid solutions—for example, putting a tracking device in one container and then using that data to help manage the rest of the shipment.
The startup’s goal is to make predictions that help companies improve the efficiency of their operations, and reduce their reliance on manual processes. “There are logistics operators with hundreds of cargo coming in every single week, they’re going and checking this manually every day. That goes into an Excel sheet and that’s what the planning of downstream operations is based off of,” said Gupta.
But the COVID-19 pandemic created an “urgent need to digitize, and it’s transformed supply chains from being a cost function to the core of getting products on time, so we work with some of the largest manufacturers as well as freight forwarders,” she added. For example, a food and beverage company in Europe sent a shipment to Taipei, a trip that usually takes about 70 days. But it took more than three months to arrive. Portcast was able to track the shipment as it moved across different ports and ships, helping its customers understand what caused the delay.
“Besides just predicting when there will be a likely disruption, we’re able to pinpoint and say there’s a delay of X days because there will likely be a typhoon or a transshipment, and that empowers them because they can tell their trucking and warehousing teams how many containers are going to come in,” said Gupta. “This reduces port fees, detention charges and the number of hours spent on manually checking different company’s websites and trying to figure out what happened to their supply chain.”
One of Portcast’s advantages over other logistics tech startups that want to fix supply chain visibility is that it launched out of the Asia-Pacific region, where ships usually go through multiple ports and have to work around frequent weather events like tropical storms and typhoons. The technology Portcast developed to create shorter voyages between Singapore and Malaysia (for example) is also applicable to intercontinental routes like Asia and Europe, or Asia and the United States.
“Our technology is global in scale and that allows us to compete against other players in this market,” said Gupta. “The other thing that differentiates us is that we work not just with manufacturers, but also with shipping companies, logistics companies and cargo airlines, and that allows us to create network effects. There is a really strong synergy between what’s happening in ocean freight and air freight, and that allows us to understand patterns in the industry and creates leverage for any other company that comes onto our platform.
Portcast’s future plans include moving from predictive AI to include prescriptive AI within the next two quarters. Right now, the platform can tell companies what is causing delays, but prescriptive AI will also enable it to make automated suggestions. For example, it can tell clients what ports are faster, other ships and modes of transport that can help them get around a disruption and how to optimize their capacity.
The company is also planning to launch Order Visiblity by the end of this year, a feature that will track containers filled with a specific item. Consumer prices for many different kinds of products are rising, due in part to overwhelmed supply chains. By enabling companies to track specific SKUs in real-time, Portcast can not only help items arrive more quickly, but also show how much CO2 emissions each shipment creates.
“Carbon offsetting or carbon trading can only happen once you have visibility into how much you are actually spending, and that’s the piece we can get involved in,” said Gupta. “By allowing predictions like, for example, if you will arrive early, that’s an opportunity for a shipping company to slow down and save fuel like bunker fuel, which not only brings an immense amount of savings, but also reduces CO2 emissions.
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H2O Hospitality secures $30M Series C to expedite hotel digital transformation
The pandemic has triggered more demand for contactless and staff-less operations in the hospitality sector, and now H2O Hospitality, the unmanned hotel management company, has closed a $30 million round on the back of that boost. The South Korea and Japan-based startup automates front and backend processes including accommodation reservation, room management and front desk duties, and it will be using the funds to continue expanding its business.
The Series C round (equivalent to about 34 billion won) is being led by Kakao Investment and Korea Development Bank (KDB), Gorilla Private Equity, Intervest and NICE Investment also participated. With Southeast Asia’s joint fund, Kejora-Intervest Growth Fund also joined in the round, it is a sign that H2O Hospitality will be focusing specifically on the Southeast Asian Market. H2O Hospitality has raised $7 million Series B round from Samsung Ventures, Stonebridge Ventures, IMM Investment and Shinhan Capital in February 2020.
H2O Hospitality will expand its business further by adding various types of accommodations in South Korea and Japan in 2021 and 2022 and plans to enter Singapore and Indonesia in 4Q in 2022 in line with its Southeast Asia penetration strategy, according to H2O Hospitality co-founder and CEO John Lee.
“H2O Hospitality is currently speaking with several global hotel chain companies to partner with their digital transformation and operation outside of Korea and Japan,” Lee told TechCrunch.
H2O will invest in R&D to advance its customer channel solutions and contactless check-in systems depending on customer needs of each country in Asia, Lee continued.
“We need optimal system development and customization for each accommodation and situation to lead successful hotel digital transformation even after COVID-19,” Lee said in an email interview.
H2O Hospitality was founded in South Korea 2015 by CEO John Lee, and it has been on something of an acquisition-expansion spree. It entered Japan in 2017, for example, by acquiring several Japanese hospitality management companies. In 2021, H2O acquired two South Korean companies such as the contactless hotel solution company, ImGATE, and a local creator startup, Replace, in order to enhance its technology and ESG competence.
These days, the company operates approximately 7,500 accommodations including hotels, ryokans and guest houses, in Tokyo, Osaka, Seoul, Busan, and Bangkok.
H2O Hospitality’s Information and Communications Technology (ICT)-based hotel management system, which enables hotel management to automate and digitize, includes the Channel Management System (CMS), Property Management System (PMS), Room Management System (RMS), and Facility Management System (FMS).
Its integrated hotel management system can reduce hotel management’s fixed operating costs by 50%, while increasing revenue by as much as 20%, according to its statement.
“COVID-19 hit the hospitality industry the most and most of the hotels wanted to decrease their fixed cost level, but it was impossible with their current operational flow,” Lee continued, “They had to go through digital transformation”.
When asked how the pandemic affected H2O as COVID-19 still freezes most of the tourism industry, Lee said H2O’s revenue has been increased by as much as 30% before the pandemic, but that percentage has been dropped to 5-15% post COVID-19. Revenue drivers these days are based around tools it’s built to improve the efficiency of its customers. They include its automated dynamic pricing (ADR) tool and diverse sales channels like online and offline travel agencies in domestic and overseas, he said.
Lee also pointed out that H2O has been onboarding a lot of properties and that has also contributed to H2O’s revenue growth in the last 18 months. H2O was the only company in Asia, he claims, and many property owners have started to get onboard since August 2020, he explained.
“Every single hotel that we onboarded during the pandemic turned around their profits & losses statements and started to recover their financial loss,” Lee said.
There are currently about 16.4 million hotel rooms in the world that generate $570 billion a year, according to Lee. H2O believes that it can digitize all the lodging accommodations in the world as the company’s main goal is not building a hotel brand but allowing hotel owners to operate their properties with better operation, he said.
Lee explained that the current hotel operation process looks a lot like that of “2G phones”, that was at a stage before turning to smartphones, and H2O is turning the overall hotel operation into a “smartphone”.
“This is a very natural transition for the (hospitality) industry as it was also natural for the cellphone users to transit from 2G phone to smartphone,” Lee said.
Unfortunately, the cross-border inbound tourism market has still been stopped for both Korea and Japan even though each domestic market is still pumping demand for the market, Lee mentioned.
“We believe the inbound tourism market will recover within a year as the vaccinations grow for both countries (Korea and Japan),” Lee said.
Managing Director at Kejora-Intervest Growth Fund Jun-seok Kang told TechCrunch: “We knew this new wave for hotel digital transformation trend was coming even before the pandemic; however, COVID-19 definitely expedited the transition period, and we believe H2O will thrive in the transforming hotel market.”
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Fractory raises $9M to rethink the manufacturing supply chain for metalworks
The manufacturing industry took a hard hit from the Covid-19 pandemic, but there are signs of how it is slowly starting to come back into shape — helped in part by new efforts to make factories more responsive to the fluctuations in demand that come with the ups and downs of grappling with the shifting economy, virus outbreaks and more. Today, a businesses that is positioning itself as part of that new guard of flexible custom manufacturing — a startup called Fractory — is announcing a Series A of $9 million (€7.7 million) that underscores the trend.
The funding is being led by OTB Ventures, a leading European investor focussed on early growth, post-product, high-tech start-ups, with existing investors Trind Ventures, Superhero Capital, United Angels VC, Startup Wise Guys and Verve Ventures also participating.
Founded in Estonia but now based in Manchester, England — historically a strong hub for manufacturing in the country, and close to Fractory’s customers — Fractory has built a platform to make it easier for those that need to get custom metalwork to upload and order it, and for factories to pick up new customers and jobs based on those requests.
Fractory’s Series A will be used to continue expanding its technology, and to bring more partners into its ecosystem.
To date, the company has worked with more than 24,000 customers and hundreds of manufacturers and metal companies, and altogether it has helped crank out more than 2.5 million metal parts.
To be clear, Fractory isn’t a manufacturer itself, nor does it have no plans to get involved in that part of the process. Rather, it is in the business of enterprise software, with a marketplace for those who are able to carry out manufacturing jobs — currently in the area of metalwork — to engage with companies that need metal parts made for them, using intelligent tools to identify what needs to be made and connecting that potential job to the specialist manufacturers that can make it.
The challenge that Fractory is solving is not unlike that faced in a lot of industries that have variable supply and demand, a lot of fragmentation, and generally an inefficient way of sourcing work.
As Martin Vares, Fractory’s founder and MD, described it to me, companies who need metal parts made might have one factory they regularly work with. But if there are any circumstances that might mean that this factory cannot carry out a job, then the customer needs to shop around and find others to do it instead. This can be a time-consuming, and costly process.
“It’s a very fragmented market and there are so many ways to manufacture products, and the connection between those two is complicated,” he said. “In the past, if you wanted to outsource something, it would mean multiple emails to multiple places. But you can’t go to 30 different suppliers like that individually. We make it into a one-stop shop.”
On the other side, factories are always looking for better ways to fill out their roster of work so there is little downtime — factories want to avoid having people paid to work with no work coming in, or machinery that is not being used.
“The average uptime capacity is 50%,” Vares said of the metalwork plants on Fractory’s platform (and in the industry in general). “We have a lot more machines out there than are being used. We really want to solve the issue of leftover capacity and make the market function better and reduce waste. We want to make their factories more efficient and thus sustainable.”
The Fractory approach involves customers — today those customers are typically in construction, or other heavy machinery industries like ship building, aerospace and automotive — uploading CAD files specifying what they need made. These then get sent out to a network of manufacturers to bid for and take on as jobs — a little like a freelance marketplace, but for manufacturing jobs. About 30% of those jobs are then fully automated, while the other 70% might include some involvement from Fractory to help advise customers on their approach, including in the quoting of the work, manufacturing, delivery and more. The plan is to build in more technology to improve the proportion that can be automated, Vares said. That would include further investment in RPA, but also computer vision to better understand what a customer is looking to do, and how best to execute it.
Currently Fractory’s platform can help fill orders for laser cutting and metal folding services, including work like CNC machining, and it’s next looking at industrial additive 3D printing. It will also be looking at other materials like stonework and chip making.
Manufacturing is one of those industries that has in some ways been very slow to modernize, which in a way is not a huge surprise: equipment is heavy and expensive, and generally the maxim of “if it ain’t broke, don’t fix it” applies in this world. That’s why companies that are building more intelligent software to at least run that legacy equipment more efficiently are finding some footing. Xometry, a bigger company out of the U.S. that also has built a bridge between manufacturers and companies that need things custom made, went public earlier this year and now has a market cap of over $3 billion. Others in the same space include Hubs (which is now part of Protolabs) and Qimtek, among others.
One selling point that Fractory has been pushing is that it generally aims to keep manufacturing local to the customer to reduce the logistics component of the work to reduce carbon emissions, although as the company grows it will be interesting to see how and if it adheres to that commitment.
In the meantime, investors believe that Fractory’s approach and fast growth are strong signs that it’s here to stay and make an impact in the industry.
“Fractory has created an enterprise software platform like no other in the manufacturing setting. Its rapid customer adoption is clear demonstrable feedback of the value that Fractory brings to manufacturing supply chains with technology to automate and digitise an ecosystem poised for innovation,” said Marcin Hejka in a statement. “We have invested in a great product and a talented group of software engineers, committed to developing a product and continuing with their formidable track record of rapid international growth
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Mobius Labs nabs $6M to help more sectors tap into computer vision
Berlin-based Mobius Labs has closed a €5.2 million (~$6.1M) funding round off the back of increased demand for its computer vision training platform. The Series A investment is led by Ventech VC, along with Atlantic Labs, APEX Ventures, Space Capital, Lunar Ventures plus some additional angel investors.
The startup offers an SDK that lets the user create custom computer vision models fed with a little of their own training data — as an alternative to off-the-shelf tools which may not have the required specificity for a particular use-case.
It also flags a ‘no code’ focus, saying its tech has been designed with a non-technical user in mind.
As it’s an SDK, Mobius Labs’ platform can also be deployed on premise and/or on device — rather than the customer needing to connect to a cloud service to tap into the AI tool’s utility.
“Our custom training user interface is very simple to work with, and requires no prior technical knowledge on any level,” claims Appu Shaji, CEO and chief scientist.
“Over the years, a trend we have observed is that often the people who get the maximum value from AI are non technical personas like a content manager in a press and creative agency, or an application manager in the space sector. Our no-code AI allows anyone to build their own applications, thus enabling these users to get close to their vision without having to wait for AI experts or developer teams to help them.”
Mobius Labs — which was founded back in 2018 — now has 30 customers using its tools for a range of use cases.
Uses include categorisation, recommendation, prediction, reducing operational expense, and/or “generally connecting users and audiences to visual content that is most relevant to their needs”. (Press and broadcasting and the stock photography sector have unsurprisingly been big focuses to date.)
But it reckons there’s wider utility for its tech and is gearing up for growth.
It caters to businesses of various sizes, from startups to SMEs, but says it mainly targets global enterprises with major content challenges — hence its historical focus on the media sector and video use cases.
Now, though, it’s also targeting geospatial and earth observation applications as it seeks to expand its customer base.
The 30-strong startup has more than doubled in size over the last 18 months. With the new funding it’s planning to double its headcount again over the next 12 months as it looks to expand its geographical footprint — focusing on Europe and the US.
Year-on-year growth has also been 2x but it believes it can dial that up by tapping into other sectors.
“We are working with industries that are rich in visual data,” says Shaji. “The geospatial sector is something that we are focussing on currently as we have a strong belief that vast amounts of visual data is being produced by them. However, these huge archives of raw pixel data are useless on their own.
“For instance, if we want to track how river fronts are expanding, we have to look at data collected by satellites, sort and tag them in order to analyse them. Currently this is being done manually. The technology we are creating comes in a lightweight SDK, and can be deployed directly into these satellites so that the raw data can be detected and then analysed by machine learning algorithms. We are currently working with satellite companies in this sector.”
On the competitive front, Shaji names Clarifai and Google Cloud Vision as the main rivals it has in its sights.
“We realise these are the big players but at the same time believe that we have something unique to offer, which these players cannot: Unlike their solutions, our platform users can be outside the field of computer vision. By democratising the training of machine learning models beyond simply the technical crowd, we are making computer vision accessible and understandable by anyone, regardless of their job titles,” he argues.
“Another core value that differentiates us is the way we treat client data. Our solutions are delivered in the form of a Software Development Kit (SDK), which runs on-premise, completely locally on clients’ systems. No data is ever sent back to us. Our role is to empower people to build applications, and make them their own.”
Computer vision startups have been a hot acquisition target in recent years and some earlier startups offering ‘computer vision as a service’ got acquired by IT services firms to beef up their existing offerings, while tech giants like Amazon and (the aforementioned) Google offer their own computer vision services too.
But Shaji suggests the tech is now at a different stage of development — and primed for “mass adoption”.
“We’re talking about providing solutions that empower clients to build their own applications,” he says, summing up the competitive play. “And that [do that] with complete data privacy, where our solutions run on-premise, and we don’t see our clients data. Coupled with that is the ease of use that our technology offers: It is a lightweight solution that can be deployed on many ‘edge’ devices like smartphones, laptops, and even on satellites.”
Commenting on the funding in a statement, Stephan Wirries, partner at Ventech VC, added: “Appu and the team at Mobius Labs have developed an unparalleled offering in the computer vision space. Superhuman Vision is impressively innovative with its high degree of accuracy despite very limited required training to recognise new objects at excellent computational efficiency. We believe industries will be transformed through AI, and Mobius Labs is the European Deep Tech innovator teaching machines to see.”
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Singapore-based caregiving startup Homage raises $30M Series C
Homage, the caregiving-focused startup, has raised a $30 million Series C led by Sheares Healthcare Group, which is wholly-owned by investment firm Temasek. Other participants included new investors DG Daiwa Ventures and Sagana Capital, and returning backers East Ventures (Growth), HealthXCapital, SeedPlus, Trihill Capital and Alternate Ventures.
The new funding will be used to develop Homage’s technology, continue integrating with aged and disability care payer and provider infrastructure and speed-up its regional expansion through partnerships with hospitals and care providers. Homage currently operates in Singapore, Malaysia and Australia.
The Singapore-based company’s services include home visits from caregivers, nurses, therapists and doctors; telemedicine; and services for chronic illnesses. One of the reasons Homage’s platform is able to scale up is its matching engine, which helps clients, like older adults and people living with chronic conditions, find providers who are best suited to their needs (the final matches are made by Homage’s team).
The startup says the round was oversubscribed and one of the largest fundings raised by an on-demand care platform in Southeast Asia and Oceania so far. It brings Homage’s total raised to more than $45 million.
As part of Series C, Sheares Healthcare Group chief corporate development officer Khoo Ee Ping will join Homage’s board of directors.
Homage now has a regional network of more than 6,000 pre-screened and trained care professionals. It claims that its business outside of Singapore has grown more than 600% year-over-year in 2021, and it has more than tripled revenue over the past year.
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The time Animoto almost brought AWS to its knees
Today, Amazon Web Services is a mainstay in the cloud infrastructure services market, a $60 billion juggernaut of a business. But in 2008, it was still new, working to keep its head above water and handle growing demand for its cloud servers. In fact, 15 years ago last week, the company launched Amazon EC2 in beta. From that point forward, AWS offered startups unlimited compute power, a primary selling point at the time.
EC2 was one of the first real attempts to sell elastic computing at scale — that is, server resources that would scale up as you needed them and go away when you didn’t. As Jeff Bezos said in an early sales presentation to startups back in 2008, “you want to be prepared for lightning to strike, […] because if you’re not that will really generate a big regret. If lightning strikes, and you weren’t ready for it, that’s kind of hard to live with. At the same time you don’t want to prepare your physical infrastructure, to kind of hubris levels either in case that lightning doesn’t strike. So, [AWS] kind of helps with that tough situation.”
An early test of that value proposition occurred when one of their startup customers, Animoto, scaled from 25,000 to 250,000 users in a 4-day period in 2008 shortly after launching the company’s Facebook app at South by Southwest.
At the time, Animoto was an app aimed at consumers that allowed users to upload photos and turn them into a video with a backing music track. While that product may sound tame today, it was state of the art back in those days, and it used up a fair amount of computing resources to build each video. It was an early representation of not only Web 2.0 user-generated content, but also the marriage of mobile computing with the cloud, something we take for granted today.
For Animoto, launched in 2006, choosing AWS was a risky proposition, but the company found trying to run its own infrastructure was even more of a gamble because of the dynamic nature of the demand for its service. To spin up its own servers would have involved huge capital expenditures. Animoto initially went that route before turning its attention to AWS because it was building prior to attracting initial funding, Brad Jefferson, co-founder and CEO at the company explained.
“We started building our own servers, thinking that we had to prove out the concept with something. And as we started to do that and got more traction from a proof-of-concept perspective and started to let certain people use the product, we took a step back, and were like, well it’s easy to prepare for failure, but what we need to prepare for success,” Jefferson told me.
Going with AWS may seem like an easy decision knowing what we know today, but in 2007 the company was really putting its fate in the hands of a mostly unproven concept.
“It’s pretty interesting just to see how far AWS has gone and EC2 has come, but back then it really was a gamble. I mean we were talking to an e-commerce company [about running our infrastructure]. And they’re trying to convince us that they’re going to have these servers and it’s going to be fully dynamic and so it was pretty [risky]. Now in hindsight, it seems obvious but it was a risk for a company like us to bet on them back then,” Jefferson told me.
Animoto had to not only trust that AWS could do what it claimed, but also had to spend six months rearchitecting its software to run on Amazon’s cloud. But as Jefferson crunched the numbers, the choice made sense. At the time, Animoto’s business model was for free for a 30 second video, $5 for a longer clip, or $30 for a year. As he tried to model the level of resources his company would need to make its model work, it got really difficult, so he and his co-founders decided to bet on AWS and hope it worked when and if a surge of usage arrived.
That test came the following year at South by Southwest when the company launched a Facebook app, which led to a surge in demand, in turn pushing the limits of AWS’s capabilities at the time. A couple of weeks after the startup launched its new app, interest exploded and Amazon was left scrambling to find the appropriate resources to keep Animoto up and running.
Dave Brown, who today is Amazon’s VP of EC2 and was an engineer on the team back in 2008, said that “every [Animoto] video would initiate, utilize and terminate a separate EC2 instance. For the prior month they had been using between 50 and 100 instances [per day]. On Tuesday their usage peaked at around 400, Wednesday it was 900, and then 3,400 instances as of Friday morning.” Animoto was able to keep up with the surge of demand, and AWS was able to provide the necessary resources to do so. Its usage eventually peaked at 5000 instances before it settled back down, proving in the process that elastic computing could actually work.
At that point though, Jefferson said his company wasn’t merely trusting EC2’s marketing. It was on the phone regularly with AWS executives making sure their service wouldn’t collapse under this increasing demand. “And the biggest thing was, can you get us more servers, we need more servers. To their credit, I don’t know how they did it — if they took away processing power from their own website or others — but they were able to get us where we needed to be. And then we were able to get through that spike and then sort of things naturally calmed down,” he said.
The story of keeping Animoto online became a main selling point for the company, and Amazon was actually the first company to invest in the startup besides friends and family. It raised a total of $30 million along the way, with its last funding coming in 2011. Today, the company is more of a B2B operation, helping marketing departments easily create videos.
While Jefferson didn’t discuss specifics concerning costs, he pointed out that the price of trying to maintain servers that would sit dormant much of the time was not a tenable approach for his company. Cloud computing turned out to be the perfect model and Jefferson says that his company is still an AWS customer to this day.
While the goal of cloud computing has always been to provide as much computing as you need on demand whenever you need it, this particular set of circumstances put that notion to the test in a big way.
Today the idea of having trouble generating 3,400 instances seems quaint, especially when you consider that Amazon processes 60 million instances every day now, but back then it was a huge challenge and helped show startups that the idea of elastic computing was more than theory.
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