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Tape It launches an AI-powered music recording app for iPhone
Earlier this year, Apple officially discontinued Music Memos, an iPhone app that allowed musicians to quickly record audio and develop new song ideas. Now, a new startup called Tape It is stepping in to fill the void with an app that improves audio recordings by offering a variety of features, including higher-quality sound, automatic instrument detection, support for markers, notes and images, and more.
The idea for Tape It comes from two friends and musicians, Thomas Walther and Jan Nash.
Walther had previously spent three and a half years at Spotify, following its 2017 acquisition of the audio detection startup Sonalytic, which he had co-founded. Nash, meanwhile, is a classically trained opera singer, who also plays bass and is an engineer.
They’re joined by designer and musician Christian Crusius, previously of the design consultancy Fjord, which was acquired by Accenture.
The founders, who had played in a band together for many years, were inspired to build Tape It because it was something they wanted for themselves, Walther says. After ending his stint at Spotify working in their new Soundtrap division (an online music startup Spotify also bought in 2017), he knew he wanted to work on a project that was more focused on the music-making side of things. But while Soundtrap worked for some, it wasn’t what either Walther or his friends had needed. Instead, they wanted a simple tool that would allow them to record their music with their phone — something that musicians often do today using Apple’s Voice Memos app and, briefly, Music Memos — until its demise.
Image Credits: Tape It
“Regardless of whether you’re an amateur or even like a touring professional…you will record your ideas with your phone, just because that’s what you have with you,” Walther explains. “It’s the exact same thing with cameras — the best camera is the one you have with you. And the best audio recording tool is the one you have with you.”
That is, when you want to record, the easiest thing to do is not to get out your laptop and connect a bunch of cables to it, then load up your studio software — it’s to hit the record button on your iPhone.
The Tape It app allows you to do just that, but adds other features that make it more competitive with its built-in competition, Voice Memos.
When you record using Tape It, the app leverages AI to automatically detect the instrument, then annotate the recording with a visual indication to make those recordings easier to find by looking for the colorful icon. Musicians can also add their own markers to the files right when they record them, then add notes and photos to remind themselves of other details. This can be useful when reviewing the recordings later on, Walther says.
Image Credits: Tape It
“If I have a nice guitar sound, I can just take a picture of the settings on my amplifier, and I have them. This is something musicians do all the time,” he notes. “It’s the easiest way to re-create that sound.”
Another novel, but simple, change in Tape It is it that breaks longer recordings into multiple lines, similar to a paragraph of text. The team calls this the “Time Paragraph,” and believes it will make listening to longer sessions easier than the default — which is typically a single, horizontally scrollable recording.
Image Credits: Tape It
The app has also been designed so it’s easier to go back to the right part of recordings, thanks to its smart waveforms, in addition to the optional markers and photos. And you can mark recordings as favorites so you can quickly pull up a list of your best ideas and sounds. The app offers full media center integration as well, so you can play back your music whenever you have time.
However, the standout feature is Tape It’s support for “Stereo HD” quality. Here, the app takes advantage of the two microphones on devices like the iPhone XS, XR, and other newer models, then improves the sound using AI technology and other noise reduction techniques, which it’s developed in-house. This feature is part of its $20 per year premium subscription.
Over time, Tape It intends to broaden its use of AI and other IP to improve the sound quality further. It also plans to introduce collaborative features and support for importing and exporting recordings into professional studio software. This could eventually place Tape It into the same market that SoundCloud had initially chased before it shifted its focus to becoming more of a consumer-facing service.
But first, Tape It wants to nail the single-user workflow before adding on more sharing features.
“We decided that it’s so important to make sure it’s useful, even just for you. The stuff that you can collaborate on — if you don’t like using it yourself, you’re not going to use it,” Walther says.
Tape It’s team of three is based in Stockholm and Berlin and is currently bootstrapping.
The app itself is a free download on iOS and will later support desktop users on Mac and Windows. An Android version is not planned.
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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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Data scientists: don’t be afraid to explore new avenues
I’m a native French data scientist who cut his teeth as a research engineer in computer vision in Japan and later in my home country. Yet I’m writing from an unlikely computer vision hub: Stuttgart, Germany.
But I’m not working on German car technology, as one would expect. Instead, I found an incredible opportunity mid-pandemic in one of the most unexpected places: An ecommerce-focused, AI-driven, image-editing startup in Stuttgart focused on automating the digital imaging process across all retail products.
My experience in Japan taught me the difficulty of moving to a foreign country for work. In Japan, having a point of entry with a professional network can often be necessary. However, Europe has an advantage here thanks to its many accessible cities. Cities like Paris, London, and Berlin often offer diverse job opportunities while being known as hubs for some specialties.
While there has been an uptick in fully remote jobs thanks to the pandemic, extending the scope of your job search will provide more opportunities that match your interest.
Search for value in unlikely places, like retail
I’m working at the technology spin-off of a luxury retailer, applying my expertise to product images. Approaching it from a data scientist’s point of view, I immediately recognized the value of a novel application for a very large and established industry like retail.
Europe has some of the most storied retail brands in the world — especially for apparel and footwear. That rich experience provides an opportunity to work with billions of products and trillions of dollars in revenue that imaging technology can be applied to. The advantage of retail companies is a constant flow of images to process that provides a playing ground to generate revenue and possibly make an AI company profitable.
Another potential avenue to explore are independent divisions typically within an R&D department. I found a significant number of AI startups working on a segment that isn’t profitable, simply due to the cost of research and the resulting revenue from very niche clients.
Companies with data are companies with revenue potential
I was particularly attracted to this startup because of the potential access to data. Data by itself is quite expensive and a number of companies end up working with a finite set. Look for companies that directly engage at the B2B or B2C level, especially retail or digital platforms that affect front-end user interface.
Leveraging such customer engagement data benefits everyone. You can apply it towards further research and development on other solutions within the category, and your company can then work with other verticals on solving their pain points.
It also means there’s massive potential for revenue gains the more cross-segments of an audience the brand affects. My advice is to look for companies with data already stored in a manageable system for easy access. Such a system will be beneficial for research and development.
The challenge is that many companies haven’t yet introduced such a system, or they don’t have someone with the skills to properly utilize it. If you finding a company isn’t willing to share deep insights during the courtship process or they haven’t implemented it, look at the opportunity to introduce such data-focused offerings.
In Europe, the best bets involve creating automation processes
I have a sweet spot for early-stage companies that give you the opportunity to create processes and core systems. The company I work for was still in its early days when I started, and it was working towards creating scalable technology for a specific industry. The questions that the team was tasked with solving were already being solved, but there were numerous processes that still had to be put into place to solve a myriad of other issues.
Our year-long efforts to automate bulk image editing taught me that as long as the AI you’re building learns to run independently across multiple variables simultaneously (multiple images and workflows), you’re developing a technology that does what established brands haven’t been able to do. In Europe, there are very few companies doing this and they are hungry for talent who can.
So don’t be afraid of a little culture shock and take the leap.
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LOVE unveils a modern video messaging app with a business model that puts users in control
A London-headquartered startup called LOVE, valued at $17 million following its pre-seed funding, aims to redefine how people stay in touch with close family and friends. The company is launching a messaging app that offers a combination of video calling as well as asynchronous video and audio messaging, in an ad-free, privacy-focused experience with a number of bells and whistles, including artistic filters and real-time transcription and translation features.
But LOVE’s bigger differentiator may not be its product alone, but rather the company’s mission.
LOVE aims for its product direction to be guided by its user base in a democratic fashion as opposed to having the decisions made about its future determined by an elite few at the top of some corporate hierarchy. In addition, the company’s longer-term goal is ultimately to hand over ownership of the app and its governance to its users, the company says.
These concepts have emerged as part of bigger trends towards a sort of “Web 3.0,” or next phase of internet development, where services are decentralized, user privacy is elevated, data is protected and transactions take place on digital ledgers, like a blockchain, in a more distributed fashion.
LOVE’s founders are proponents of this new model, including serial entrepreneur Samantha Radocchia, who previously founded three companies and was an early advocate for the blockchain as the co-founder of Chronicled, an enterprise blockchain company focused on the pharmaceutical supply chain.
As someone who’s been interested in emerging technology since her days of writing her anthropology thesis on currency exchanges in “Second Life’s” virtual world, she’s now faculty at Singularity University, where she’s given talks about blockchain, AI, Internet of Things, Future of Work, and other topics. She’s also authored an introductory guide to the blockchain with her book “Bitcoin Pizza.”
Co-founder Christopher Schlaeffer, meanwhile, held a number of roles at Deutsche Telekom, including chief product & innovation officer, corporate development officer and chief strategy officer, where he along with Google execs introduced the first mobile phone to run Android. He was also chief digital officer at the telecommunication services company VEON.
The two crossed paths after Schlaeffer had already begun the work of organizing a team to bring LOVE to the public, which includes co-founders Chief Technologist Jim Reeves, also previously of VEON, and Chief Designer Timm Kekeritz, previously an interaction designer at international design firm IDEO in San Francisco, design director at IXDS and founder of design consultancy Raureif in Berlin, among other roles.
Image Credits: LOVE
Explained Radocchia, what attracted her to join as CEO was the potential to create a new company that upholds more positive values than what’s often seen today — in fact, the brand name “LOVE” is a reference to this aim. She was also interested in the potential to think through what she describes as “new business models that are not reliant on advertising or harvesting the data of our users,” she says.
To that end, LOVE plans to monetize without any advertising. While the company isn’t ready to explain its business model in full, it would involve users opting in to services through granular permissions and membership, we’re told.
“We believe our users will much rather be willing to pay for services they consciously use and grant permissions to in a given context than have their data used for an advertising model which is simply not transparent,” says Radocchia.
LOVE expects to share more about the model next year.
As for the LOVE app itself, it’s a fairly polished mobile messenger offering an interesting combination of features. Like any other video chat app, you can video call with friends and family, either in one-on-one calls or in groups. Currently, LOVE supports up to five call participants, but expects to expand that as it scales. The app also supports video and audio messaging for asynchronous conversations. There are already tools that offer this sort of functionality on the market, of course — like WhatsApp, with its support for audio messages, or video messenger Marco Polo. But they don’t offer quite the same expanded feature set.
Image Credits: LOVE
For starters, LOVE limits its video messages to 60 seconds, for brevity’s sake. (As anyone who’s used Marco Polo knows, videos can become a bit rambling, which makes it harder to catch up when you’re behind on group chats.) In addition, LOVE allows you to both watch the video content as well as read the real-time transcription of what’s being said — the latter which comes in handy not only for accessibility’s sake, but also for those times you want to hear someone’s messages but aren’t in a private place to listen or don’t have headphones. Conversations can also be translated into 50 languages.
“A lot of the traditional communication or messenger products are coming from a paradigm that has always been text-based,” explains Radocchia. “We’re approaching it completely differently. So while other platforms have a lot of the features that we do, I think that…the perspective that we’ve approached it has completely flipped it on its head,” she continues. “As opposed to bolting video messages on to a primarily text-based interface, [LOVE is] actually doing it in the opposite way and adding text as a sort of a magically transcribed add-on — and something that you never, hopefully, need to be typing out on your keyboard again,” she adds.
The app’s user interface, meanwhile, has been designed to encourage eye-to-eye contact with the speaker to make conversations feel more natural. It does this by way of design elements where bubbles float around as you’re speaking and the bubble with the current speaker grows to pull your focus away from looking at yourself. The company is also working with the curator of Serpentine Gallery in London, Hans Ulrich-Obrist, to create new filters that aren’t about beautification or gimmicks, but are instead focused on introducing a new form of visual expression that makes people feel more comfortable on camera.
For the time being, this has resulted in a filter that slightly abstracts your appearance, almost in the style of animation or some other form of visual arts.
The app claims to use end-to-end encryption and the automatic deletion of its content after seven days — except for messages you yourself recorded, if you’ve chosen to save them as “memorable moments.”
“One of our commitments is to privacy and the right-to-forget,” says Radocchia. “We don’t want to be or need to be storing any of this information.”
LOVE has been soft-launched on the App Store, where it’s been used with a number of testers and is working to organically grow its user base through an onboarding invite mechanism that asks users to invite at least three people to join. This same onboarding process also carefully explains why LOVE asks for permissions — like using speech recognition to create subtitles.
LOVE says its valuation is around $17 million USD following pre-seed investments from a combination of traditional startup investors and strategic angel investors across a variety of industries, including tech, film, media, TV and financial services. The company will raise a seed round this fall.
The app is currently available on iOS, but an Android version will arrive later in the year. (Note that LOVE does not currently support the iOS 15 beta software, where it has issues with speech transcription and in other areas. That should be resolved next week, following an app update now in the works.)
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Privacy-oriented search app Xayn raises $12M from Japanese backers to go into devices
Back in December 2020 we covered the launch of a new kind of smartphone app-based search engine, Xayn.
“A search engine?!” I hear you say? Well, yes, because despite the convenience of modern search engines’ ability to tailor their search results to the individual, this user-tracking comes at the expense of privacy. This mass surveillance might be what improves Google’s search engine and Facebook’s ad targeting, to name just two examples, but it’s not very good for our privacy.
Internet users are admittedly able to switch to the U.S.-based DuckDuckGo, or perhaps France’s Qwant, but what they gain in privacy, they often lose in user experience and the relevance of search results, through this lack of tailoring.
What Berlin-based Xayn has come up with is personalized, but a privacy-safe web search on smartphones, which replaces the cloud-based AI employed by Google et al. with the innate AI in-built into modern smartphones. The result is that no data about you is uploaded to Xayn’s servers.
And this approach is not just for “privacy freaks”. Businesses that need search but don’t need Google’s dominant market position are increasingly attracted by this model.
And the evidence comes today with the news that Xayn has now raised almost $12 million in Series A funding led by the Japanese investors Global Brain and KDDI (a Japanese telecommunications operator), with participation from previous backers, including the Earlybird VC in Berlin. Xayn’s total financing now comes to more than $23 million.
It would appear that Xayn’s fusion of a search engine, a discovery feed and a mobile browser has appealed to these Asian market players, particularly because Xayn can be built into OEM devices.
The result of the investment is that Xayn will now also focus on the Asian market, starting with Japan, as well as Europe.
Leif-Nissen Lundbæk, co-founder and CEO of Xayn said: “We proved with Xayn that you can have it all: great results through personalization, privacy by design through advanced technology and a convenient user experience through clean design.”
He added: “In an industry in which selling data and delivering ads en masse are the norm, we choose to lead with privacy instead and put user satisfaction front and center.”
The funding comes as legislation such as the EU’s GDPR or California’s CCPA have both raised public awareness about personal data online.
Since its launch, Xayn says its app has been downloaded around 215,000 times worldwide, and a web version of its app is expected soon.
Over a call, Lundbæk expanded on the KDDI aspect of the fund-raising: “The partnership with KDDI means we will give users access to Xayn for free, while the corporate — such as KDDI — is the actual customer but gives our search engine away for free.”
The core features of Xayn include personalized search results; a personalized feed of the entire internet, which learns from their Tinder-like swipes, without collecting or sharing personal data; and an ad-free experience.
Naoki Kamimeada, partner at Global Brain Corporation said: “The market for private online search is growing, but Xayn is head and shoulders above everyone else because of the way they’re re-thinking how finding information online should be.”
Kazuhiko Chuman, head of KDDI Open Innovation Fund, said: “This European discovery engine uniquely combines efficient AI with a privacy-protecting focus and a smooth user experience. At KDDI, we’re constantly on the lookout for companies that can shape the future with their expertise and technology. That’s why it was a perfect match for us.”
In addition to the three co-founders (Leif-Nissen Lundbæk, chief executive officer, Professor Michael Huth, chief research officer, and Felix Hahmann, chief operations officer), Dr Daniel von Heyl will come on board as chief financial officer. Frank Pepermans will take on the role of chief technology officer and Michael Briggs will join as chief growth officer.
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Vaayu’s carbon tracking for retailers raises $1.6M, claims it could cut CO2 in half by 2030
Carbon tracking is very much the new hot thing in tech, and we’ve previously covered more generalist startups doing this at scale for companies, such as Plan A Earth out of Berlin.
But there’s clearly an opportunity to get deep into a vertical sector and tailor solutions to it.
That’s the plan of Vaayu, a carbon tracking platform aimed specifically at retailers. It has now raised $1.57 million in pre-seed funding in a round led by CapitalT. Several angels also took part, including Atomico’s Angel Program, Planet Positive LP, Saarbrücker 21, Expedite Ventures and NP-Hard Ventures.
Carbon tracking for the retail fashion industry, in particular, is urgently needed. Unfortunately, the fashion industry remains responsible for 10% of annual global carbon emissions, which ads up to more than all international flights and maritime shipping combined.
Vaayu says it integrates with various point-of-sale systems, such as Shopify and Webflow. It then pulls in data on logistics, operations and packaging to monitor, measure and reduce their carbon emissions. Normally, retailers calculate emissions once a year, which is obviously far less accurate.
Vaayu was founded in 2020 by Namrata Sandhu (CEO), former head of Sustainability at fashion retailer Zalando, as well as Anita Daminov (CPO) and Luca Schmid (CTO). Vaayu currently has 25 global brand customers, including Missoma, Armed Angels and Organic Basics.
Commenting on the fundraise, Sandhu said: “We have only nine short years left to achieve the UN’s goal of reducing carbon emissions by 50% by 2030 and as the third-largest contributor to global emissions, retailers need to take action — and fast. Vaayu is here to help retailers measure, monitor, and reduce their carbon footprint at scale across the entire supply chain — something that I know from my own experience can be complex and expensive.”
Speaking to me over a call, Sandhu told me: “Putting the focus on retail basically allows us to automate the calculation, which means in three clicks you can get your carbon footprint right away. That then allows us to really get accurate data, and with that, we can basically do reductions specific to the business but using software, rather than any kind of manual intervention or a kind of ‘intermediate’ state where you need to put together an Excel sheet. Because we focus on retail we can automate the entire process and also automate the reductions.”
“We are delighted to be backed by female-led CapitalT who understood us and our vision right from the start. We look forward to developing Vaayu further in the coming months so we can reach as many retailers as possible and help put the brakes on the impending climate crisis,” she added.
Janneke Niessen, founding partner, CapitalT commented: “We are very excited to join Vaayu on their mission to reduce carbon emission for retailers worldwide. The Vaayu product is very scalable and its quick and easy implementation allows for fast adoption. We are confident that with this experienced team, Vaayu will soon be one of the fastest-growing climate tech companies in Europe and the world.”
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Accel closes on $3B across three funds as it ramps up global investing
Accel announced Tuesday the close of three new funds totaling $3.05 billion, money that it will be using to back early-stage startups, as well as growth rounds for more mature companies. Notably, the 38-year-old Silicon Valley-based venture firm is doubling down on global investing.
The announcement underscores both the robust confidence investors continue to have for backing startups in the tech sector and the amount of money available to startups these days.
Specifically, today Accel is announcing its 15th early-stage U.S. fund at $650 million; its seventh early-stage European and Israeli fund also at $650 million and its sixth global growth stage fund at $1.75 billion. The latter fund is in addition, and designed to complement, a previously unannounced $2.3 billion global “Leaders” fund that is focused on later-stage investing that Accel closed in December.
Accel expects to invest in about 20 to 30 companies per fund on average, according to Partner Rich Wong. Its average investment in its growth fund will be in the $50 million to $75 million range, and $75 million and $100 million out of its global Leaders fund.
But the firm is also still eager and “excited” to incubate companies, Wong said.
“We’ll still write $500,000 to $1 million seed checks,” he told TechCrunch. “It’s important to us to work with companies from the very beginning and support them through their entire journey.”
Indeed, as TechCrunch recently reported, Accel has a history of backing companies that were previously bootstrapped (and often profitable) -– the latest example being Lower, a Columbus, Ohio-based fintech, which just raised a $100 million Series A.
Interestingly, Accel is often referred to some of these companies by existing portfolio companies (also in the case of Lower, whose CEO was referred to Accel by Galileo Clay Wilkes). More often than not, companies that Accel backs out of its early-stage and growth funds are bootstrapped and located outside of Silicon Valley.
The venture firm has long looked outside of Silicon Valley for opportunities, and has had offices not only in the Bay Area, but in London and Bangalore for years. Part of its investment thesis is to “invest early and locally,” according to Wong. Examples of this philosophy include investments in companies based all over the world — from Mexico to Stockholm to Tel Aviv to Munich.
Since the time of its last fund closure in 2019, the firm has seen 10 portfolio companies go public, including Slack, Austin-based Bumble, Bucharest-based UiPath, CrowdStrike, PagerDuty, Deliveroo and Squarespace, among others.
It also had 40 companies experience an M&A, including Utah-based Qualtrics’s $8 billion acquisition by SAP and Segment’s $3.2 billion acquisition by Twilio. Also, just last week, Rockwell Automation announced it was buying Michigan-based Plex Systems for $2.22 billion in cash. Accel first invested in Plex, which has developed a subscription-based smart manufacturing platform, in 2012.
Recent investments include a number of fintech companies such as LatAm’s Flink, Berlin-based Trade Republic, Unit and Robinhood rival Public. Accel has also backed as existing portfolio companies such as Webflow, a software company that helps businesses build no-code websites and events startup Hopin.
Wong says Accel is “open-minded but thematic” in its investment approach.
Accel Partner Sonali de Rycker, who is based out of London, agrees.
“For example, we’ll look at automation companies, consumer businesses and security companies, but at a global scale. Our goal is to find the best entrepreneurs regardless of where they are,” she said.
That has only been intensified by the recent rise of the smartphone and cloud, Wong said.
“Before, companies were mostly selling to the consumer in their own country,” he added. “But now the size of the market is so dramatically bigger, allowing them to become even larger, which is one of the reasons why I believe we’re seeing investment pace at this speed.”
To support this, it’s notable that Accel’s global Leaders fund is “dramatically” larger than the $500 million Leaders fund the firm closed in 2019.
Also, de Rycker points out, companies are staying private longer so the opportunity to invest in them until they sell or go public is greater.
Accel is also patient. In some cases, the firm’s investors will develop “years-long” relationships with companies they are courting.
“1Password is an example of this approach,” Wong said. “Arun [Mathew] had that relationship for at least six years before that investment was made. Finally, 1Password called and said ‘We’re ready, and we want you to do it.’ ”
And so Accel led the Canadian company’s first external round of funding in its 14-year history — a $200 million Series A — in 2019.
While the firm is open-minded, there are still some industries it has not yet embraced as much as others. For example, Wong said, “We’re not announcing a $2.2 billion crypto fund, but we have done crypto investments, and see some very interesting trends there. We’ll look at where crypto takes us.”
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Berlin’s Bryter raises $66M to take its no-code tools for enterprises to the US
No-code startups continue to see a lot of traction among enterprises, where employees — strictly speaking, non-technical, but still using software every day — are getting hands-on and building apps to take on some of the more repetitive aspects of their jobs, the so-called “citizen coders” of the working world.
And in one of the latest developments, Bryter — an AI-based no-code startup that has built a platforms used by some 100 global enterprises to date across some 2,000 business applications and workflows — is announcing a new round of funding to double down on that opportunity. The Berlin-based company has closed a Series B of $66 million, money that it will be investing into its platform and expanding in the U.S. out of a New York office it opened last year. The funding comes on the heels of seeing a lot of demand for its tools, CEO and co-founder Michael Grupp said in an interview.
“It was a great year for low-code and no-code platforms,” said Grupp, who co-founded the company with Micha-Manuel Bues and Michael Hübl. “What everyone has realized is that most people don’t actually care about the tech. They only care about the use cases. They want to get things done.” Customers using the service include the likes of McDonald’s, Telefónica, PwC, KPMG and Deloitte in Europe, as well as banks, healthcare and industrial enterprises.
Tiger Global is leading this round, with previous backers Accel, Dawn Capital, Notion Capital and Cavalry Ventures also participating, along with a number of individual backers (they include Amit Agarwal, CPO of Datadog; Lars Björk, former CEO of Qlik; Ulf Zetterberg, founder and CEO of Seal Software; and former ServiceNow global SVP James Fitzgerald). The valuation is not being disclosed; Bryter has raised around $90 million to date.
Accel and Dawn co-led Bryter’s Series A of $16 million less than a year ago, in June 2020, a rapid funding pace that underscores both interest in the no-code/low-code space — Bryter’s enterprise customer base has doubled from 50 since then — and the fact that startups in it are striking while the iron is hot.
Bryter’s not the only one: Airtable, Genesis, Rows, Creatio and Ushur are among the many startups building “hands-on tech creation for non-techie people” that have raised money in the last several months.
Automation has been the bigger trend that has propelled a lot of this activity. Knowledge workers spend most of their time these days in apps — a state of affairs that pre-dates the COVID-19 pandemic, but has definitely been furthered throughout it. While some of that work still requires manual involvement and evaluation from those workers, software has automated large swathes of those jobs.
RPA — robotic process automation, where companies like UiPath, Automation Anywhere and Blue Prism have taken a big lead — has accounted for a significant chunk of that activity, especially when it comes to reading forms and lots of data entry. But there remains a lot of other transactions and activities within specific apps where RPA is typically not used (not yet at least!). And this is where non-tech workers are finding that no-code tools like Bryter, which use artificial intelligence to deliver more personalised, yet scalable, automation, can play a very useful role.
“We sit on top of RPA in many cases,” said Grupp.
The company says that business functions where its platform has been implemented include compliance, legal, tax, privacy and security, procurement, administration and HR, and the kinds of features that are being built include virtual assistants, chatbots, interactive self-service tools and more.
These don’t replace people as such, but cut down the time they need to spend in specific tasks to process and handle information within them, and could in theory also be used to build tools for customers to interact with services more easily, cutting down on the amount of time that agents are getting details and handling engagements.
That scalability and the rapid customer up-take from a pool of users that extends beyond tech early adopters are part of what attracted the funding.
“Bryter has all the characteristics of a top-tier software company: high quality product that solves a real customer pain point, a large market opportunity and a world-class founding team,” said John Curtius, a partner at Tiger Global, in a statement. “The feedback from Bryter’s customers was resoundingly positive in our research, and we are excited to see the company reach new heights over the coming years.”
“Bryter has seen explosive growth over the last year, signing landmark customers across a large number of sectors and use cases. This does not come as a surprise. In the pandemic-affected world, digitalisation is no longer a nice to have, it is an imperative,” added Evgenia Plotnikova, a partner at Dawn Capital.
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No-code business intelligence service y42 raises $2.9M seed round
Berlin-based y42 (formerly known as Datos Intelligence), a data warehouse-centric business intelligence service that promises to give businesses access to an enterprise-level data stack that’s as simple to use as a spreadsheet, today announced that it has raised a $2.9 million seed funding round led by La Famiglia VC. Additional investors include the co-founders of Foodspring, Personio and Petlab.
The service, which was founded in 2020, integrates with more than 100 data sources, covering all the standard B2B SaaS tools, from Airtable to Shopify and Zendesk, as well as database services like Google’s BigQuery. Users can then transform and visualize this data, orchestrate their data pipelines and trigger automated workflows based on this data (think sending Slack notifications when revenue drops or emailing customers based on your own custom criteria).
Like similar startups, y42 extends the idea data warehouse, which was traditionally used for analytics, and helps businesses operationalize this data. At the core of the service is a lot of open source and the company, for example, contributes to GitLabs’ Meltano platform for building data pipelines.
y42 founder and CEO Hung Dang. Image Credits: y42
“We’re taking the best of breed open-source software. What we really want to accomplish is to create a tool that is so easy to understand and that enables everyone to work with their data effectively,” Y42 founder and CEO Hung Dang told me. “We’re extremely UX obsessed and I would describe us as a no-code/low-code BI tool — but with the power of an enterprise-level data stack and the simplicity of Google Sheets.”
Before y42, Vietnam-born Dang co-founded a major events company that operated in more than 10 countries and made millions in revenue (but with very thin margins), all while finishing up his studies with a focus on business analytics. And that in turn led him to also found a second company that focused on B2B data analytics.
Image Credits: y42
Even while building his events company, he noted, he was always very product- and data-driven. “I was implementing data pipelines to collect customer feedback and merge it with operational data — and it was really a big pain at that time,” he said. “I was using tools like Tableau and Alteryx, and it was really hard to glue them together — and they were quite expensive. So out of that frustration, I decided to develop an internal tool that was actually quite usable and in 2016, I decided to turn it into an actual company. ”
He then sold this company to a major publicly listed German company. An NDA prevents him from talking about the details of this transaction, but maybe you can draw some conclusions from the fact that he spent time at Eventim before founding y42.
Given his background, it’s maybe no surprise that y42’s focus is on making life easier for data engineers and, at the same time, putting the power of these platforms in the hands of business analysts. Dang noted that y42 typically provides some consulting work when it onboards new clients, but that’s mostly to give them a head start. Given the no-code/low-code nature of the product, most analysts are able to get started pretty quickly — and for more complex queries, customers can opt to drop down from the graphical interface to y42’s low-code level and write queries in the service’s SQL dialect.
The service itself runs on Google Cloud and the 25-people team manages about 50,000 jobs per day for its clients. The company’s customers include the likes of LifeMD, Petlab and Everdrop.
Until raising this round, Dang self-funded the company and had also raised some money from angel investors. But La Famiglia felt like the right fit for y42, especially due to its focus on connecting startups with more traditional enterprise companies.
“When we first saw the product demo, it struck us how on top of analytical excellence, a lot of product development has gone into the y42 platform,” said Judith Dada, general partner at LaFamiglia VC. “More and more work with data today means that data silos within organizations multiply, resulting in chaos or incorrect data. y42 is a powerful single source of truth for data experts and non-data experts alike. As former data scientists and analysts, we wish that we had y42 capabilities back then.”
Dang tells me he could have raised more but decided that he didn’t want to dilute the team’s stake too much at this point. “It’s a small round, but this round forces us to set up the right structure. For the Series A, which we plan to be towards the end of this year, we’re talking about a dimension which is 10x,” he told me.
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German insurtech platform Hepster raises $10M Series A led by Element Ventures
Hepster, an insurtech platform from Germany, has raised $10 million in a Series A funding round led by Element Ventures. Also participating was Seventure Partners, MBMV and GPS Ventures, as well as previous investors. The funds will be used to broaden the Hepster insurance ecosystem and scale up its network, with an emphasis on automation.
The German insurance market is famously slow at adopting new practices, and Hepster is part of a new wave of insurtech startups in the country taking advantage of this. It allows businesses to build insurance policies from scratch, matched specifically to the needs of their individual service or industry. E-commerce players, for instance, can then embed these insurance products into the e-commerce journey.
Its products are therefore better suited to the new sector of, for example, shared e-bike schemes and peer-to-peer rental platforms, which are rarely covered by traditional brokers in Germany. However, it also caters to traditional, established industries as well.
It now has more than 700 partners, including European bike retailers and rental companies Greenstorm Mobility and Baron Mobility, as well as Berlin-based cargo bike provider Citkar and Munich e-bike startup SUSHI.
Christian Range, Hepster co-founder and CEO, said in a statement: “Hepster is now a key player within the European insurance market. Our state-of-the-art technology with our API-driven ecosystem, as well as our highly service-oriented approach, sets us apart.”
In an interview he told me: “Germany is the toughest market with the most regulations, the most laws. We have a saying in Germany, if you can make it in Germany, you can make it everywhere. Also, it’s a big market in terms of selling insurance products because Germans really like insurance in every regard. So there is huge market potential in Germany I think.”
Michael McFadgen, partner at Element Ventures, said: “As new industries and business models emerge, companies need much more flexible insurance propositions than what is currently being offered by traditional brokers. Hepster is the breakout company in the space, and their focus on embedded insurance will pay dividends in years to come.”
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