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Greycroft, Lerer Hippeau and Audible back audio measurement startup Veritonic
Veritonic is announcing that it has raised $3.2 million in Series A funding led by Greycroft, with participation from Lerer Hippeau and Amazon-owned audiobook service Audible.
CEO Scott Simonelli, who founded the New York startup with COO Andrew Eisner and CTO Kevin Marshall, told me that his goal is to create a new category of “audio intelligence” — namely, measuring and predicting the effectiveness of any piece of audio content or advertising.
The company is focused on marketing initially, with its first product, Creative Measurement, analyzing any audio ad and showing marketers how it scores compared to similar content, as well as identifying which parts of the audio are most effective. And Veritonic is launching a new product, Competitive Intelligence, which helps businesses see how and where their competitors are spending on advertising and provides alerts when those competitors launch a new ad.
Simonelli said that until now, audio measurement has been limited to things like creating audience panels with a few hundred people, which simply doesn’t scale, given the enormous growth in the audio market.
Veritonic, on the other hand, has analyzed thousands of audio files, correlating the content with data about how people responded and using that analysis to predict how people will respond to new audio. Simonelli said the company can add more “fuel” by going out and gathering more human response data, but even without additional data, it can provide an instant prediction on an ad or campaign’s effectiveness.
Image Credits: Veritonic
Simonelli also noted that Veritonic has spent the past five years developing technology that’s specifically attuned to the challenges of measuring audio effectiveness — like the fact that audio is experienced over time and, even more than other media, needs to be memorable.
“We can look at a sonic profile and predict and evaluate how somebody is going to respond,” he said.
The ultimate goal, he added, is to create the “benchmark for audio advertising,” which means working with a variety of players in the industry. For example, he said that when you look at other audio investments in Greycroft’s portfolio (such as podcast network Wondery or podcast analytics company Podsights): “Veritonic makes every one of those audio investments more valuable.”
Veritonic’s made pretty good progress on that goal already, with partners including Pandora, SiriusXM and NPR, and brand clients like Pepsi, Visa and Subway. It was previously backed by Newark Venture Partners (whose founder Don Katz previously founded Audible).
“We are excited to be a part of Veritonic’s continued growth and success,” said Greycroft’s Alan Patricof in a statement. “I’m personally very passionate about the future of voice, and the team at Veritonic deeply understands how to use audio to drive recall, stickiness and brand awareness — which is hugely important in a highly-competitive consumer brand landscape.”
Simonelli added that Veritonic will use the new funding to expand its data science and sales teams. Eventually, he hopes to start analyzing non-advertising content as well — for example, since Audible is an investor, he said, “Analyzing every audiobook on the planet is something we’re ready for and excited to do.”
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YC grad DigitalBrain snags $3.4M seed to streamline customer service tasks
Most startup founders have a tough road to their first round of funding, but the founders of Digital Brain had it a bit tougher than most. The two young founders survived by entering and winning hackathons to pay their rent and put food on the table. One of the ideas they came up with at those hackathons was DigitalBrain, a layer that sits on top of customer service software like Zendesk to streamline tasks and ease the job of customer service agents.
They ended up in Y Combinator in the Summer 2020 class, and today the company announced a $3.4 million seed investment. This total includes $3 million raised this round, which closed in August, and previously unannounced investments of $250,000 in March from Unshackled Ventures and $150,000 from Y Combinator in May.
The round was led by Moxxie Ventures, with help from Caffeinated Capital, Unshackled Ventures, Shrug Capital, Weekend Fund, Underscore VC and Scribble Ventures, along with a slew of individual investors.
Company co-founder Kesava Kirupa Dinakaran says that after he and his partner Dmitry Dolgopolov met at a hackathon in May 2019, they moved into a community house in San Francisco full of startup founders. They kept hearing from their housemates about the issues their companies faced with customer service as they began scaling. Like any good entrepreneur, they decided to build something to solve that problem.
“DigitalBrain is an external layer that sits on top of existing help desk software to actually help the support agents get through their tickets twice as fast, and we’re doing that by automating a lot of internal workflows, and giving them all the context and information they need to respond to each ticket, making the experience of responding to these tickets significantly faster,” Dinakaran told TechCrunch.
What this means in practice is that customer service reps work in DigitalBrain to process their tickets, and as they come upon a problem such as canceling an order or reporting a bug, instead of traversing several systems to fix it, they choose the appropriate action in DigitalBrain, enter the required information and the problem is resolved for them automatically. In the case of a bug, it would file a Jira ticket with engineering. In the case of canceling an order, it would take all of the actions and update all of the records required by this request.
As Dinakaran points out, they aren’t typical Silicon Valley startup founders. They are 20-year-old immigrants from India and Russia, respectively, who came to the U.S. with coding skills and a dream of building a company. “We are both outsiders to Silicon Valley. We didn’t go to college. We don’t come from families of means. We wanted to come here and build our initial network from the ground up,” he said.
Eventually they met some folks through their housemates, who suggested that they apply to Y Combinator. “As we started to meet people that we met through our community house here, some of them were YC founders and they kept saying I think you guys will love the YC community, not just in terms of your ethos, but also just purely from a perspective of meeting new people and where you are,” he said.
He said while he and his co-founder have trouble wrapping their arms around a number like the amount they have in the bank now, considering it wasn’t that long ago that they were struggling to meet expenses every month, they recognize this money buys them an opportunity to help start building a more substantial company.
“What we’re trying to do is really accelerate the development and building of what we’re doing. And we think if we push the gas pedal with the resources we’ve gotten, we’ll be able to accelerate bringing on the next couple of customers, and start onboarding some of the larger companies we’re interested in,” he said.
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Tone raises $4M to help e-commerce brands text with their customers
While many companies are using chatbots and other forms of automation to manage their communication with customers, Boston-based Tone is betting that humans will remain a key part of the equation.
“The traditional models of bots and humans is, ‘Hello, I’m a bot, now you get to battle with me to finally get to a human,’ ” said Tone CEO Tivan Amour. “Our version of that is, ‘I’m a human using AI to get you the answers you need more quickly.’ ”
Amour and his co-founders Vlad Pick and Kyle Weidman previously created a bicycle startup called Fortified Bicycle, and he said they “figured out that the best way to close our customers on these $750 to $1,000 orders was to actually engage them in text message conversations.”
After all, when it comes to “high consideration” purchases like bicycles, people usually want to discuss their questions and concerns with another human being. Over time, the Fortified team built what Amour said was a “semi-automated system” to help its sales team stay on top of these conversations.
“We started bragging to our friends about it, ‘You’ve gotta do this, it’s the future of mobile commerce,’ ” he recalled. “And they’d say, ‘Okay, that’s cool, but we don’t have any of the systems of doing that, we don’t have the salespeople.’ ”
Tone’s founders
So after selling Fortified Bicycle, Amour and Pick created Tone to help any e-commerce business manage similar text message conversations. Tone employs its own team of human agents to actually do the texting, assisted by software that helps them find the information they need.
It integrates with e-commerce systems like Shopify and Magento, and it’s already working with more than 1,000 brands like ThirdLove, Peak Design and Usual Wines — which are seeing as much as a 26% increase in revenue and a 15% increase in order size.
Amour also noted that specific Tone agents are assigned to specific brands, which means that customers will be talking to the same person whenever they have a question for that business. In some cases, customers have been talking to the same agent for months or years. (Update: Tone clarified that this isn’t a person, but a single persona that’s probably an amalgamation of multiple agents.)
“Particularly in a post-COVID world, it’s pretty clear that online shopping has become the dominant form of shopping, but I think nobody has thought about how you replace that human experience that you get in traditional retail,” he said.
Tone is announcing today that it has raised $4 million in seed funding led by Bling Capital, with participation from Day One Ventures, One Way Ventures, TIA Ventures and executives from Google, Facebook, Dropbox and Uber.
With the new funding, Amour said Tone will be able to build out the “relationship automation” aspect of the product. He also suggested that the platform could eventually expand beyond text messaging, but it sounds like that’s not a big priority.
“In theory, we’re a conversational sales platform more than we are an SMS company,” he said. “However there are a bunch of trends right now [such as the growth of mobile commerce] that make SMS the most obvious place for this sort of innovation.”
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Writer pens a $5M seed round for its AI style guide that flags bias and tone
Anyone who writes online or in a word processor has likely gotten used to the inevitable squiggly line denoting a misspelled word or clumsy phrase. But what if you use a word that’s loaded, a phrase that’s too formal or not formal enough, or refer to a group of people in an outdated way? Writer is a service that watches as you type, flagging language that doesn’t match up with your style guide and values, and it just raised $5 million to scale up.
Both people and the companies they work for want to improve the way they write, but not just in terms of grammar and spelling. If a company says it’s inclusive, but the language in its press releases or internal blogs are peppered with anachronisms and bias, it suggests their concern only goes so far.
“Companies are hungry to put actions behind their words,” said Writer founder and CEO May Habib. “They want to be able to tell a consistent story to their users everywhere that they’re interacting with them. What Writer does is let people know when they’re using insensitive language, or things that could be considered negative, and let companies set brand guidelines.”
Right off the bat let us admit that there is a whiff of the sinister about the idea of a company dictating how its employees speak, though that’s nothing new when it comes to content and official communications. But this isn’t about controlling speech for power — it’s about recognizing that we are all flawed communicators and could use a hand keeping ourselves honest. Less thought police and more a well-informed angel sitting on your shoulder whispering things like, “Hey. Are you sure you want to describe that lawyer as ‘exotic’?”
Examples of things Writer checks for. Image Credits: Writer
There are tons of slip-ups we all make along those lines; less obvious, but no less potentially offensive. It’s important in public communications, among other things, to refer to a group by the term they prefer, not the first one that pops into your head; Writer has up-to-date libraries of this information sourced from the communities themselves. Some phrases may have become politically loaded in the last couple of years, but you’re not aware; no problem, it has alternatives. You want to avoid unnecessarily gendered language, great, but everyone slips up now and then; Writer can spot it — or make the connection with previous pronouns to make sure you don’t, for example, gender an anonymous source.
Accusations of “political correctness” will dog the service, but as Habib put it: “This is beyond politics; this is about respect for people who live a certain way, or are a certain way, and prefer to use certain terms. We’re trying to help companies create communities of belonging.” And as we’ve seen over and over again in tech, there is often a serious disconnect between the stated aspiration of a company and how people are treated within them. Just using the right words is a pretty low bar to start with, honestly.
Image Credits: Writer
Writer isn’t just a growing blacklist of words you should think twice about using, though. The natural language processing engine at the heart of it is also very concerned with things like sentence complexity, paragraph length and tone. It has to have this deeper understanding, Habib explained, because “it’s not enough to underline — you need to know what to replace it with, and when you replace it, you need to fit it into the sentence. These are actually hard NLP problems.”
That lets it fit into a variety of roles in addition to promoting inclusive language. It can watch for the usual spelling and grammar mistakes, as well as things like formality, active voice, “liveliness” (whatever that is, I don’t have it) and other metrics that help define a brand.
And of course you can bring in your own style guide so your editors don’t have to roll their eyes at serial commas in headlines, double dashes instead of em dashes, e-mail instead of email and all the rest of the little nips and tucks that keep a brand’s writing in a generally recognizable shape.
Image Credits: Writer
The service can also switch between style guides or adjust or disable itself in different apps and sites — so internal emails aren’t given the same guidelines as press releases, or a blog post’s style can be differentiated from a newsletter’s.
Obviously Grammarly is a big competitor here, but Habib feels that it and the growing number of in-browser or in-app checking services are very focused on the technical piece. Writer is less about preventing an individual writer’s errors, and more about creating consistency among groups of writers and making sure they are working from the same high-level linguistic standards.
Of course security is also a concern — no one wants a keylogger running on their machine, however helpful it may be. Habib was careful to emphasize that Writer runs locally in the browser as a plug-in, integrating with Word or Chrome for now but with other apps and services on the way. “None of that data ever hits a writer server, and no metadata — all the processing is done in the text area,” she said. The only data that’s sent back is the fact that a given suggestion was used, such as changing “should of” to “should have” or “illegal aliens” to “undocumented immigrants.” No user data is used to train the models and no content apart from the correction itself is sent or stored on Writer’s servers.
Writer is available now, for $11/person/month (with the obligatory free trial period, of course) for a basic version and some unspecified amount for enterprise deals with multiple style guides, plagiarism detection, and so on. It’s only available in English, and although there is of course demand for the service in other languages, the depth of the NLP model and the specificity of what it recognizes to the language mean it does not generalize well. To take on Spanish or Korean would be to develop an entirely new product. So English it is for now.
The company is new, and has been developing its NLP engine (on the back of a previous effort, which monitored user-facing language in GitHub repos) for 18 months in something like stealth. The $5 million seed round, led by Upfront Ventures, Aspect Ventures, Bonfire Ventures, and Broadway Angels should help the company scale, though it already has some top-tier, household-name customers, so with that and the money, its immediate future seems to be secure.
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With $18M in new funding, Braintrust says it’s creating a fairer model for freelancers
Braintrust, a network for freelance technical and design talent that launched over the summer, is announcing that it has raised $18 million in new funding.
Co-founder and CEO Adam Jackson has written for TechCrunch about how tech companies need to treat independent contractors with more empathy. He told me via email that the San Francisco-based startup is making that idea a reality by offering a very different approach than existing marketplaces for freelance work.
For one thing, Braintrust only charges the companies doing the hiring — freelancers won’t have to pay to join or to bid on a project, and Braintrust won’t charge a fee on their project payments. In addition, the startup is using a cryptocurrency token that it calls Btrust to reward users who build the network, for example by inviting new customers or vetting freelancers. Apparently, the token will give users a stake in how the network evolves in the future.
“Just imagine if Uber had given all of its drivers some ownership in the company what a different company it would be today,” Jackson said. “Braintrust will be 100% user-owned. Everyone who participates on the platform has skin in the game.”
And for companies, Braintrust is supposed to allow them to tap freelancers for work that they’d normally do in-house. The startup’s clients already include Nestlé, Pacific Life, Deloitte, Porsche, Blue Cross Blue Shield and TaskRabbit.
According to Jackson, most of the talent on the platform consists of career freelancers, but with many people losing their jobs during the COVID-19 pandemic, “we’ve seen an influx of talent coming looking to join the ranks of the freelancers.”
He added that the startup already became profitable after raising its $6 million seed round, so the new funding will allow it to build the core team and also bring in more work.
“We exist to help companies accelerate their product roadmaps and innovation, and this injection of funding will help us do just that,” Jackson said.
The new funding was led by ACME and Blockchange, with participation from new investors Pantera, Multicoin and Variant.
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Altinity grabs $4M seed to build cloud version of ClickHouse open-source data warehouse
Earlier this month, cloud data warehouse Snowflake turned heads when it debuted on the stock market. Today, Altinity, the commercial company behind the open-source ClickHouse data warehouse, announced a $4 million seed round from Accel along with a new cloud service, Altinity.Cloud.
“Fundamentally, the company started out as an open-source services bureau offering support, training and [custom] engineering features into ClickHouse. And what we’re doing now with this investment from Accel is we’re extending it to offer a cloud platform in addition to the other things that we already have,” CEO Robert Hodges told TechCrunch.
As the company describes it, “Altinity.Cloud offers immediate access to production-ready ClickHouse clusters with expert enterprise support during every aspect of the application life cycle.” It also helps with application design and implementation and production assistance, in essence combining the consulting side of the house with the cloud service.
The company was launched in 2017 by CTO Alexander Zaitsev, who was one of the early adopters of ClickHouse. Up until now the startup has been bootstrapped with revenue from the services business.
Hodges came on board last year after a stint at VMware because he saw a company with tremendous potential, and his background in cloud services made him a good person to lead the company as it built the cloud product and moved into its next phase.
ClickHouse at its core is a relational database that can run in the cloud or on-prem with big improvements in performance, Hodges says. And he says that developers are enamored with it because you can start a project on a laptop and scale it up from there.
“We’re very simple to operate, just a single binary. You can start from a Docker image. You can run it anywhere, literally anywhere that Linux runs, from an Intel Nuc all the way up to clusters with hundreds of nodes,” Hodges explained.
The investment from Accel should help them finish building the cloud product, which has been in private beta since July, while helping them build a sales and marketing operation to help sell it to the target enterprise market. The startup currently has 27 people, with plans to hire 15 more.
Hodges says that he wants to build a diverse and inclusive company, something he says the tech industry in general has failed at achieving. He believes that one of the reasons for that is the requirement of a computer science degree, which he says has created “a gate for women and people of color,” and he thinks by hiring people with more diverse backgrounds, you can build a more diverse company.
“So one of the things that’s high up on my list is to get back to a more equitable and diverse population of people working on this thing,” he said.
Over time, the company sees the cloud business overtaking the consulting arm in terms of revenue, but that aspect of the business will always have a role in the revenue mix because this is complex by its nature, even with a cloud service.
“Customers can’t just do it entirely by having a push-button interface. They will actually need humans that work with them, and help them understand how to frame problems, help them understand how to build applications that take care of that […] And then finally, help them deal with problems that naturally arise when you’re when you’re in production,” he said.
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Golden raises $14.5M to build a wiki-style database of tech knowledge
Golden is announcing that it has raised $14.5 million in Series A funding. The round was led by previous investor Andreessen Horowitz, with the firm’s co-founder Marc Andreessen joining the startup’s board of directors.
When Golden launched last year, founder and CEO Jude Gomila told me that his goal was to create a knowledge base focused on areas where Wikipedia’s coverage is often spotty, particularly emerging technology and startups.
Gomila told me this week that “companies, technologies and the people involved in them” remain Golden’s strength. In that sense, you could see it as a competitor to Crunchbase, but with a much bigger emphasis on explaining and “clustering” information on big topics like quantum computing and COVID-19, rather than just aggregating key data about companies and people. (By the way, both TechCrunch and the author of this post have their own profile pages, though the latter is woefully empty.)
In contrast to Wikipedia, which relies on community editors, Gomila said most of the data in Golden is gathered using artificial intelligence and natural language processing: “We’re using AI to extract information from the news, from websites, from public databases.
This is supplemented by Golden staff (former TechCrunch copy editor Holden Page leads the startup’s research team), while the larger community can also pitch in by flagging things that are incorrect or need to be updated. (As one example of this “human in the loop” editing process, Gomila showed me a tool where someone could paste in an article link and Golden would automatically summarize it.)
“The ultimate aim is to try and automate as much of this as possible,” Gomila said. “[For now,] this hybrid is the most effective method.”
Golden has also started working with paying customers including private equity firms, hedge funds, VCs, biotechnology companies, corporate innovation offices and government agencies — in fact, it says it signed a $1 million contract with the U.S. Air Force this year. These customers are paying for access to Golden’s research engine, which includes the company’s Query Tool and the ability to request that the startup prepare research on a particular topic.
Golden has now raised a total of $19.5 million. Other investors in the new funding include DCVC, Harpoon Ventures and Gigafund .
“Golden’s knowledge base and research engine aggregates information about emerging technologies and the companies, investors, and the builders behind them,” Andreessen said in a statement. “Human and machine intelligence, working together on Golden’s platform, results in knowledge which gives people the edge in making decisions and navigating uncertainty.”
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Coralogix lands $25M Series B to rethink log analysis and monitoring
Logging and monitoring tends to be an expensive endeavor because of the sheer amount of data involved. Companies are therefore forced to pick and choose what they monitor, limiting what they can see. Coralogix wants to change that by offering a more flexible pricing model, and today the company announced a $25 million Series B and a new real-time analytics solution called Streama.
First the funding. The round was led by Red Dot Capital Partners and O.G. Tech Ventures, with help from existing investors Aleph VC, StageOne Ventures, Janvest Capital Partners and 2B Angels. Today’s round, which comes after the startup’s $10 million Series A last November, brings the total to $41.2 million raised, according to the company.
When we spoke to Coralogix CEO and co-founder Ariel Assaraf last year regarding the A round, he described his company as more of an intelligent applications performance monitoring with some security logging analytics.
Today, the company announced Streama, which has been in Alpha since July. Assaraf says companies can pick and choose how they monitor and pay only for the features they use. That means if a particular log is only tangentially important, a customer can set it to low priority and save money, and direct the budget toward more important targets.
As the pandemic has taken hold, he says that companies are appreciating the ability to save money on their monitoring costs, and directing those resources elsewhere in the company. “We’re basically building out this full platform that is going to be inside-centric and value-centric instead of volume or machine count-centric in its pricing model,” Assaraf said.
Assaraf differentiates his company from others out there like Splunk, Datadog and Sumo Logic, saying his is a more modern approach to the problem that simplifies the operations. “All these complicated engineering things are being abstracted away in a simple way, so that any user can very quickly create savings and demonstrate that it’s [no longer] an engineering problem, it’s more of a business value question,” he explained.
Since the A round, the company has grown from 25 to 60 people spread out between Israel and the U.S. It plans to grow to 120 people in the next year with the new funding. When it comes to diversity in hiring, he says Israel is fairly homogeneous, so it involves gender parity there, something that he says he is working to achieve. The U.S. operation is still relatively small, with just 12 employees now, but it will be expanding in the next year and it’s something he says that he will need to be thinking about as he hires.
As part of that hiring spree, he wants to kick his sales and marketing operations into higher gear and start spending more on those areas as the company grows.
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Collective, a back-office platform that caters to ‘businesses of one,’ just landed a hefty seed round
Americans and other global citizens are increasingly self-employed, thanks to great software, the need for flexibility and because skilled services especially can pay fairly well, among other reasons.
In fact, exactly one year ago, the Freelancers Union and Upwork, a digital platform for freelancers, released a report estimating that 35% of the U.S. workforce had begun freelancing. With COVID-19 still making its way around the country and globe, prompting massive and continued job dislocation for many tens of millions of people, that percentage is likely to rise quickly.
Unsurprisingly, savvy startups see the economic power of these individuals — many of whom aren’t interested in managing anyone or anything other than the steady growth of their own businesses. A case in point is Collective, a 2.5-year-old, 20-person San Francisco-based startup that’s been quietly building back-office services like tax preparation and bookkeeping for what it dubs “business of one” owners, and which just closed on $8.65 million in seed funding.
General Catalyst and QED Investors co-led the round, joined by a string of renowned angel investors, including Uber cofounder Garrett Camp, Figma founder Dylan Field and DoorDash executive Gokul Rajaram.
We talked yesterday with cofounder and CEO Hooman Radfar about Collective’s mission to “empower, support and connect the self-employed community” — and what, exactly, it’s proposing.
TC: You previously founded a company and, even before it sold to Oracle in 2016, you had jumped over to VC, working with Garrett Camp at his startup studio Expa. Why shift back into founder mode?
HR: What I saw across AddThis and Expa and my angel investing is that managing finances is hard. Accounting, taxes, compliance — all that set-up as a small business is annoying.
Two years ago, [Collective cofounder] Ugur [Kaner] came into Expa and he basically pitched me on a startup-in-a-box-type program that we were talking about building from an incubation perspective, but [with more of a pointed focus on back office issues]. He’s an immigrant like me, and because he didn’t quite understand the system, he wound up having tax penalties — penalties that are even worse when you’re a freelancer. Some startups have come up with a bespoke version of what we offer, but we were like, ‘Why do they have to do it?’ These are commodities, but if you put them together in a platform, they can can be powerful.
TC: So is what you’ve created proprietary or are you working with third parties?
HR: Both. We’re an online concierge that’s focused on the back office as the core, meaning accounting and tax services. We also form an S Corp for you because you can save a lot of money [compared with forming a business as an LLC, which features different tax requirements]. So there’s an integration layer plus a dashboard on top of that. If you’re an S Corp, you need to have payroll, so we have a partnership with Gusto that comes with your subscription. We have a partnership with QuickBooks. We work with a third party on compliance. Our vision is to make this easy for you and to set this on autopilot because we understand that time is literally money.
TC: How much are you charging?
HR: For taxes, accounting, business banking and payroll, for the core package, it’s $200 a month. We are piloting bookkeeping and a fuller service package that’s probably [representative of] the direction we’ll head over time, and that will be an additional fee.
TC: How can you persuade these businesses of one that it’s worth that cost?
HR: There are almost three million people in the U.S. who [employ only themselves and] are making more than $100,000 a year and if you think about how many of these [different products] they are already using, it’s a great deal. QuickBooks and Gusto is cheaper with us. You see savings through expensing. The magic is really running your S Corp the right way. Part of that is normal income tax, but you also have a distribution and it’s taxed differently than an income — it’s taxed less. So we pull in salary data and look at expenses and across states, and say, ‘This is what we’d recommend to you based on how your cash flow is coming in, so you recognize this distribution in a compliant way.’
TC: Interesting about this useful data that you’ll be amassing from your customers. How might you use it?
HR: Our first concern is making sure the right people are seeing it [meaning we’re focused on privacy]. But there’s a lot we can do with the aggregation of that data once we’ve earned the right to use it. Among the things we could do, theoretically, includes creating a new level of scoring. If you’re a business of one, for example, it’s very difficult to get mortgages and loans, because credit agencies don’t have the tools to assess you. But if we have your financial history for years, we can represent that you’re a great person, you have a great business.
Another interesting direction as we reach more members — we’ll get to 2,000 soon — would be to use our power as a collective to get our members less expensive insurance, [help facilitate] credit, [help them with a] 401(k).
TC: There are a lot of other things you can get into presumably, too, from project management to graphic design . . .
HR: Right now, we want to make sure our core service is nailed.
Think about the transparency and peace of mind that Uber brought to ridesharing, or that Uber Eats brings to food delivery. You know when something is cooking, when it’s on its way, when it’s arriving. We’ve gotten used to that level of transparency and accountability with so many things, but when it comes to accounting, it’s not there and that’s crazy. This is your money. We want to change that.
TC: Going after “businesses of one” means you’re addressing a highly fragmented market. What kinds of partnerships are you striking to reach potential customers?
HR: We’re having those conversations now, but you can imagine neo banks make sense, along with vertical marketplaces for nurses and doctors and realtors and writers. There are a lot of possibilities.
Pictured, left to right, Collective’s cofounders: CTO Bugra Akcay, CEO Hooman Radfar and CPO Ugur Kaner.
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Datasaur snags $3.9M investment to build intelligent machine learning labeling platform
As machine learning has grown, one of the major bottlenecks remains labeling things so the machine learning application understands the data it’s working with. Datasaur, a member of the Y Combinator Winter 2020 batch, announced a $3.9 million investment today to help solve that problem with a platform designed for machine learning labeling teams.
The funding announcement, which includes a pre-seed amount of $1.1 million from last year and $2.8 million seed right after it graduated from Y Combinator in March, included investments from Initialized Capital, Y Combinator and OpenAI CTO Greg Brockman.
Company founder Ivan Lee says that he has been working in various capacities involving AI for seven years. First when his mobile gaming startup Loki Studios was acquired by Yahoo! in 2013, and Lee was eventually moved to the AI team, and, most recently, at Apple. Regardless of the company, he consistently saw a problem around organizing machine learning labeling teams, one that he felt he was uniquely situated to solve because of his experience.
“I have spent millions of dollars [in budget over the years] and spent countless hours gathering labeled data for my engineers. I came to recognize that this was something that was a problem across all the companies that I’ve been at. And they were just consistently reinventing the wheel and the process. So instead of reinventing that for the third time at Apple, my most recent company, I decided to solve it once and for all for the industry. And that’s why we started Datasaur last year,” Lee told TechCrunch.
He built a platform to speed up human data labeling with a dose of AI, while keeping humans involved. The platform consists of three parts: a labeling interface; the intelligence component, which can recognize basic things so the labeler isn’t identifying the same thing over and over; and finally a team organizing component.
He says the area is hot, but to this point has mostly involved labeling consulting solutions, which farm out labeling to contractors. He points to the sale of Figure Eight in March 2019 and to Scale, which snagged $100 million last year as examples of other startups trying to solve this problem in this way, but he believes his company is doing something different by building a fully software-based solution.
The company currently offers a cloud and on-prem solution, depending on the customer’s requirements. It has 10 employees, with plans to hire in the next year, although he didn’t share an exact number. As he does that, he says he has been working with a partner at investor Initialized on creating a positive and inclusive culture inside the organization, and that includes conversations about hiring a diverse workforce as he builds the company.
“I feel like this is just standard CEO speak, but that is something that we absolutely value in our top of funnel for the hiring process,” he said.
As Lee builds out his platform, he has also worried about built-in bias in AI systems and the detrimental impact that could have on society. He says that he has spoken to clients about the role of labeling in bias and ways of combatting that.
“When I speak with our clients, I talk to them about the potential for bias from their labelers and built into our product itself is the ability to assign multiple people to the same project. And I explain to my clients that this can be more costly, but from personal experience I know that it can improve results dramatically to get multiple perspectives on the exact same data,” he said.
Lee believes humans will continue to be involved in the labeling process in some way, even as parts of the process become more automated. “The very nature of our existence [as a company] will always require humans in the loop, […] and moving forward I do think it’s really important that as we get into more and more of the long tail use cases of AI, we will need humans to continue to educate and inform AI, and that’s going to be a critical part of how this technology develops.”
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