Y Combinator
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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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GrubMarket raises $60M as food delivery stays center stage
Companies that have leveraged technology to make the procurement and delivery of food more accessible to more people have been seeing a big surge of business this year, as millions of consumers are encouraged (or outright mandated, due to COVID-19) to socially distance or want to avoid the crowds of physical shopping and eating excursions.
Today, one of the companies that is supplying produce and other items both to consumers and other services that are in turn selling food and groceries to them, is announcing a new round of funding as it gears up to take its next step, an IPO.
GrubMarket, which provides a B2C platform for consumers to order produce and other food and home items for delivery, and a B2B service where it supplies grocery stores, meal-kit companies and other food tech startups with products that they resell, is today announcing that it has raised $60 million in a Series D round of funding.
Sources close to the company confirmed to TechCrunch that GrubMarket — which is profitable, and originally hadn’t planned to raise more than $20 million — has now doubled its valuation compared to its last round — sources tell us it is now between $400 million and $500 million.
The funding is coming from funds and accounts managed by BlackRock, Reimagined Ventures, Trinity Capital Investment, Celtic House Venture Partners, Marubeni Ventures, Sixty Degree Capital and Mojo Partners, alongside previous investors GGV Capital, WI Harper Group, Digital Garage, CentreGold Capital, Scrum Ventures and other unnamed participants. Past investors also included Y Combinator, where GrubMarket was part of the Winter 2015 cohort. For some context, GrubMarket last raised money in April 2019 — $28 million at a $228 million valuation, a source says.
Mike Xu, the founder and CEO, said that the plan remains for the company to go public (he’s talked about it before), but given that it’s not having trouble raising from private markets and is currently growing at 100% over last year, and the IPO market is less certain at the moment, he declined to put an exact timeline on when this might actually happen, although he was clear that this is where his focus is in the near future.
“The only success criteria of my startup career is whether GrubMarket can eventually make $100 billion of annual sales,” he said to me over both email and in a phone conversation. “To achieve this goal, I am willing to stay heads-down and hardworking every day until it is done, and it does not matter whether it will take me 15 years or 50 years.”
I don’t doubt that he means it. I’ll note that we had this call in the middle of the night his time in California, even after I asked multiple times if there wasn’t a more reasonable hour in the daytime for him to talk. (He insisted that he got his best work done at 4:30 a.m., a result of how a lot of the grocery business works.) Xu on the one hand is very gentle with a calm demeanor, but don’t let his quiet manner fool you. He also is focused and relentless in his work ethic.
When people talk today about buying food, alongside traditional grocery stores and other physical food markets, they increasingly talk about grocery delivery companies, restaurant delivery platforms, meal kit services and more that make or provide food to people by way of apps. GrubMarket has built itself as a profitable but quiet giant that underpins the fuel that helps companies in all of these categories by becoming one of the critical companies building bridges between food producers and those that interact with customers.
Its opportunity comes in the form of disruption and a gap in the market. Food production is not unlike shipping and other older, non-tech industries, with a lot of transactions couched in legacy processes: GrubMarket has built software that connects the different segments of the food supply chain in a faster and more efficient way, and then provides the logistics to help it run.
To be sure, it’s an area that would have evolved regardless of the world health situation, but the rise and growth of the coronavirus has definitely “helped” GrubMarket not just by creating more demand for delivered food, but by providing a way for those in the food supply chain to interact with less contact and more tech-fueled efficiency.
Sales of WholesaleWare, as the platform is called, Xu said, have seen more than 800% growth over the last year, now managing “several hundreds of millions of dollars of food wholesale activities” annually.
Underpinning its tech is the sheer size of the operation: economies of scale in action. The company is active in the San Francisco Bay Area, Los Angeles, San Diego, Seattle, Texas, Michigan, Boston and New York (and many places in between) and says that it currently operates some 21 warehouses nationwide. Xu describes GrubMarket as a “major food provider” in the Bay Area and the rest of California, with (as one example) more than 5 million pounds of frozen meat in its east San Francisco Bay warehouse.
Its customers include more than 500 grocery stores, 8,000 restaurants and 2,000 corporate offices, with familiar names like Whole Foods, Kroger, Albertson, Safeway, Sprouts Farmers Market, Raley’s Market, 99 Ranch Market, Blue Apron, Hello Fresh, Fresh Direct, Imperfect Foods, Misfit Market, Sun Basket and GoodEggs all on the list, with GrubMarket supplying them items that they resell directly, or use in creating their own products (like meal kits).
While much of GrubMarket’s growth has been — like a lot of its produce — organic, its profitability has helped it also grow inorganically. It has made some 15 acquisitions in the last two years, including Boston Organics and EJ Food Distributor this year.
It’s not to say that GrubMarket has not had growing pains. The company, Xu said, was like many others in the food delivery business — “overwhelmed” at the start of the pandemic in March and April of this year. “We had to limit our daily delivery volume in some regions, and put new customers on waiting lists.” Even so, the B2C business grew between 300% and 500% depending on the market. Xu said things calmed down by May and even as some B2B customers never came back after cities were locked down, as a category, B2B has largely recovered, he said.
Interestingly, the startup itself has taken a very proactive approach in order to limit its own workers’ and customers’ exposure to COVID-19, doing as much testing as it could — tests have been, as we all know, in very short supply — as well as a lot of social distancing and cleaning operations.
“There have been no mandates about masks, but we supplied them extensively,” he said.
So far it seems to have worked. Xu said the company has only found “a couple of employees” that were positive this year. In one case in April, a case was found not through a test (which it didn’t have, this happened in Michigan) but through a routine check and finding an employee showing symptoms, and its response was swift: the facilities were locked down for two weeks and sanitized, despite this happening in one of the busiest months in the history of the company (and the food supply sector overall).
That’s notable leadership at a time when it feels like a lot of leaders have failed us, which only helps to bolster the company’s strong growth.
“Having a proven track record of sustained hypergrowth and net income profitability, GrubMarket stands out as an extraordinarily rare Silicon Valley startup in the food technology and ecommerce segment,” said Jay Chen, managing partner of Celtic House Venture Partner. “Scaling over 15x in 4 years, GrubMarket’s creativity and capital efficiency is unmatched by anyone else in this space. Mike’s team has done an incredible job growing the company thoughtfully and sustainably. We are proud to be a partner in the company’s rapid nationwide expansion and excited by the strong momentum of WholesaleWare, their SaaS suite, which is the best we have seen in space.”
Updated with more detail on the valuation.
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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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Narrator raises $6.2M for a new approach to data modelling that replaces star schema
Snowflake went public this week, and in a mark of the wider ecosystem that is evolving around data warehousing, a startup that has built a completely new concept for modelling warehoused data is announcing funding. Narrator — which uses an 11-column ordering model rather than standard star schema to organise data for modelling and analysis — has picked up a Series A round of $6.2 million, money that it plans to use to help it launch and build up users for a self-serve version of its product.
The funding is being led by Initialized Capital along with continued investment from Flybridge Capital Partners and Y Combinator — where the startup was in a 2019 cohort — as well as new investors, including Paul Buchheit.
Narrator has been around for three years, but its first phase was based around providing modelling and analytics directly to companies as a consultancy, helping companies bring together disparate, structured data sources from marketing, CRM, support desks and internal databases to work as a unified whole. As consultants, using an earlier build of the tool that it’s now launching, the company’s CEO Ahmed Elsamadisi said he and others each juggled queries “for eight big companies single-handedly,” while deep-dive analyses were done by another single person.
Having validated that it works, the new self-serve version aims to give data scientists and analysts a simplified way of ordering data so that queries, described as actionable analyses in a story-like format — or “Narratives,” as the company calls them — can be made across that data quickly — hours rather than weeks — and consistently. (You can see a demo of how it works below provided by the company’s head of data, Brittany Davis.)
The new data-as-a-service is also priced in SaaS tiers, with a free tier for the first 5 million rows of data, and a sliding scale of pricing after that based on data rows, user numbers and Narratives in use.
Image Credits: Narrator
Elsamadisi, who co-founded the startup with Matt Star, Cedric Dussud and Michael Nason, said that data analysts have long lived with the problems with star schema modelling (and by extension the related format of snowflake schema), which can be summed up as “layers of dependencies, lack of source of truth, numbers not matching and endless maintenance,” he said.
“At its core, when you have lots of tables built from lots of complex SQL, you end up with a growing house of cards requiring the need to constantly hire more people to help make sure it doesn’t collapse.”
(We)Work Experience
It was while he was working as lead data scientist at WeWork — yes, he told me, maybe it wasn’t actually a tech company, but it had “tech at its core” — that he had a breakthrough moment of realising how to restructure data to get around these issues.
Before that, things were tough on the data front. WeWork had 700 tables that his team was managing using a star schema approach, covering 85 systems and 13,000 objects. Data would include information on acquiring buildings, to the flows of customers through those buildings, how things would change and customers might churn, with marketing and activity on social networks, and so on, growing in line with the company’s own rapidly scaling empire. All of that meant a mess at the data end.
“Data analysts wouldn’t be able to do their jobs,” he said. “It turns out we could barely even answer basic questions about sales numbers. Nothing matched up, and everything took too long.”
The team had 45 people on it, but even so it ended up having to implement a hierarchy for answering questions, as there were so many and not enough time to dig through and answer them all. “And we had every data tool there was,” he added. “My team hated everything they did.”
The single-table column model that Narrator uses, he said, “had been theorised” in the past but hadn’t been figured out.
The spark, he said, was to think of data structured in the same way that we ask questions, where — as he described it — each piece of data can be bridged together and then also used to answer multiple questions.
“The main difference is we’re using a time-series table to replace all your data modelling,” Elsamadisi explained. “This is not a new idea, but it was always considered impossible. In short, we tackle the same problem as most data companies to make it easier to get the data you want but we are the only company that solves it by innovating on the lowest-level data modelling approach. Honestly, that is why our solution works so well. We rebuilt the foundation of data instead of trying to make a faulty foundation better.”
Narrator calls the composite table, which includes all of your data reformatted to fit in its 11-column structure, the Activity Stream.
Elsamadisi said using Narrator for the first time takes about 30 minutes, and about a month to learn to use it thoroughly. “But you’re not going back to SQL after that, it’s so much faster,” he added.
Narrator’s initial market has been providing services to other tech companies, and specifically startups, but the plan is to open it up to a much wider set of verticals. And in a move that might help with that, longer term, it also plans to open source some of its core components so that third parties can build data products on top of the framework more quickly.
As for competitors, he says that it’s essentially the tools that he and other data scientists have always used, although “we’re going against a ‘best practice’ approach (star schema), not a company.” Airflow, DBT, Looker’s LookML, Chartio’s Visual SQL, Tableau Prep are all ways to create and enable the use of a traditional star schema, he added. “We’re similar to these companies — trying to make it as easy and efficient as possible to generate the tables you need for BI, reporting and analysis — but those companies are limited by the traditional star schema approach.”
So far the proof has been in the data. Narrator says that companies average around 20 transformations (the unit used to answer questions) compared to hundreds in a star schema, and that those transformations average 22 lines compared to 1,000+ lines in traditional modelling. For those that learn how to use it, the average time for generating a report or running some analysis is four minutes, compared to weeks in traditional data modelling.
“Narrator has the potential to set a new standard in data,” said Jen Wolf, Initialized Capital COO and partner and new Narrator board member, in a statement. “We were amazed to see the quality and speed with which Narrator delivered analyses using their product. We’re confident once the world experiences Narrator this will be how data analysis is taught moving forward.”
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Avo raises $3M for its analytics governance platform
Avo, a startup that helps businesses better manage their data quality across teams, today announced that it has raised a $3 million seed round led by GGV Capital, with participation from Heavybit, Y Combinator and others.
The company’s founder, Stefania Olafsdóttir, who is currently based in Iceland, was previously the head of data science at QuizUp, which at some point had 100 million users around the world. “I had the opportunity to build up the Data Science Division, and that meant the cultural aspect of helping people ask and answer the right questions — and get them curious about data — but it also meant the technical part of setting up the infrastructure and tools and pipelines, so people can get the right answers when they need it,” she told me. “We were early adopters of self-serve product analytics and culture — and we struggled immensely with data reliability and data trust.”
Image Credits: Avo
As companies collect more data across products and teams, the process tends to become unwieldy and different teams end up using different methods (or just simply different tags), which creates inefficiencies and issues across the data pipeline.
“At first, that unreliable data just slowed down decision making, because people were just like, didn’t understand the data and needed to ask questions,” Olafsdóttir said about her time at QuizUp. “But then it caused us to actually launch bad product updates based on incorrect data.” Over time, that problem only became more apparent.
“Once organizations realize how big this issue is — that they’re effectively flying blind because of unreliable data, while their competition might be like taking the lead on the market — the default is to patch together a bunch of clunky processes and tools that partially increase the level of liability,” she said. And that clunky process typically involves a product manager and a spreadsheet today.
At its core, the Avo team set out to build a better process around this, and after a few detours and other product ideas, Olafsdóttir and her co-founders regrouped to focus on exactly this problem during their time in the Y Combinator program.
Avo gives developers, data scientists and product managers a shared workspace to develop and optimize their data pipelines. “Good product analytics is the product of collaboration between these cross-functional groups of stakeholders,” Olafsdóttir argues, and the goal of Avo is to give these groups a platform for their analytics planning and governance — and to set company-wide standards for how they create their analytics events.
Once that is done, Avo provides developers with typesafe analytics code and debuggers that allows them to take those snippets and add them to their code within minutes. For some companies, this new process can help them go from spending 10 hours on fixing a specific analytics issue to an hour or less.
Most companies, the team argues, know — deep down — that they can’t fully trust their data. But they also often don’t know how to fix this problem. To help them with this, Avo also today released its Inspector product. This tool processes event streams for a company, visualizes them and then highlights potential errors. These could be type mismatches, missing properties or other discrepancies. In many ways, that’s obviously a great sales tool for a service that aims to avoid exactly these problems.
One of Avo’s early customers is Rappi, the Latin American delivery service. “This year we scaled to meet the demand of 100,000 new customers digitizing their deliveries and curbside pickups. The problem with every new software release was that we’d break analytics. It represented 25% of our Jira tickets,” said Rappi’s head of Engineering, Damian Sima. “With Avo we create analytics schemas upfront, identify analytics issues fast, add consistency over time and ensure data reliability as we help customers serve the 12+ million monthly users their businesses attract.”
As most startups at this stage, Avo plans to use the new funding to build out its team and continue to develop its product.
“The next trillion-dollar software market will be driven from the ground up, with developers deciding the tools they use to create digital transformation across every industry. Avo offers engineers ease of implementation while still retaining schemas and analytics governance for product leaders,” said GGV Capital Managing Partner Glenn Solomon. “Our investment in Avo is an investment in software developers as the new kingmakers and product leaders as the new oracles.”
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Berbix raises $9M for its identity verification platform
Berbix, an ID verification startup that was founded by former members of the Airbnb Trust and Safety team, today announced that it has raised a $9 million Series A round led by Mayfield. Existing investors, including Initialized Capital, Y Combinator and Fika Ventures, also participated in this round.
Founded in 2018, Berbix helps companies verify the identity of its users, with an emphasis on the cannabis industry, but it’s clearly not limited to this use case. Integrating the service to help online services scan and validate IDs only takes a few lines of code. In that respect, it’s not that different from payment services like Stripe, for example. Pricing starts at $99 per month with 100 included ID checks. Developers can choose a standard ID check (for $0.99 per check after the basic allotment runs out), as well as additional selfie and optional liveness checks, which ask users to show an emotion or move their head to ensure somebody isn’t simply trying to trick the system with a photo.
While ID verification may not be the first thing you think about in the context of the COVID-19 pandemic, the company is actually seeing increasing demand for its solution now that in-person ID verification has become much harder. Berbix CEO and co-founder Steve Kirkham notes that the company now processes the same number of verifications in a day that it used to do monthly only a year ago.
“The inability to conduct traditional identity checks in person has forced organizations to move online for innumerable use cases,” he says in today’s announcement. “One example is the Family Independence Initiative, a nonprofit that trusts and invests in families’ own efforts to escape poverty. Our software has enabled them to eliminate fraudulent applications and focus on the families who have been economically affected by COVID.”
Berbix co-founder Eric Levine tells me the company plans to use the new funding to expand its team, especially the product and sales department. He also noted that the team is investing heavily in localization, as well as the technical foundation of the service. In addition, it’s obviously also investing in new technologies to detect new types of fraud. Scammers never sleep, after all.
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Black founders can get tactical advice at Disrupt
In the aftermath of George Floyd’s death and widespread protests for racial justice, a number of venture capitalists made public statements about wanting to improve diversity in the tech industry — and more specifically to fund more diverse founders.
Their comments are certainly worth applauding, but actual change is a lot harder. And if it comes at all, it will take time. In the meantime, how can Black founders navigate a tech and venture capital industry where they have historically been underrepresented, overlooked and worse?
To answer that question, we’ll bring three Black founders together at Disrupt 2020 from September 14-18 who can speak directly about their experience raising funding and launching startups.
One of our speakers, Michael Seibel, is now funding startups himself as partner and CEO of startup accelerator Y Combinator. Before that, however, he was co-founder and CEO at Justin.tv (which became game streaming giant Twitch) and then at its spin-off, Socialcam (which was acquired by Autodesk). So he can talk about both sides, as both a founder and investor.
Joining Seibel will be two YC startup founders — Reham Fagiri of furniture marketplace AptDeco and Songe LaRon of barbershop software maker Squire. We’ll talk to all three of them on the Extra Crunch stage, getting as specific and tactical as possible about what Black founders can expect and what steps they can take to succeed.
Learn more at Disrupt 2020, which runs from September 14-18. Buy the Disrupt Digital Pro Pass, or if you’re an early-stage founder a Digital Startup Alley Exhibitor Package, today and get access to all the interviews on our Main Stage, workshops over on the Extra Crunch Stage, where you can get actionable tips, as well as CrunchMatch, our free, AI-powered networking platform. As soon as you register for Disrupt, you will have access to CrunchMatch and can start connecting with people. Use the tool to schedule one-on-one video calls with potential customers and investors or to recruit and interview prospective employees.
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Equity Shot: Our favorite startups from YC Demo Day
Hello and welcome back to Equity, TechCrunch’s venture capital-focused podcast (now on Twitter!), where we unpack the numbers behind the headlines.
Yep, it’s another Equity Shot. We’re back. And then we’re going to be back on Friday. Because we can’t stop talking about the biggest news week in the world of startups and venture capital in some time.
Before we start, shout-out to the NBA for the growing, wildcat strike to protest racist police violence in America.
OK, back to our regularly scheduled programming. This time ’round Natasha and your humble servant were joined by Lucas Matney, a member of the TechCrunch reporting team and a first-timer on Equity. Where’s he been all this time? Covering all sorts of things, including VR startups for the publication. He was also a big part of our coverage of both days of YC’s Demo Days, making him a perfect fit for this episode.
Danny was given a break to sit at home, play board games and iron his favorite sweatshirt. He’s back Friday morning.
In case you’ve missed the words, here’s what we wrote this week on the subject:
- All the Day One Y Combinator startups
- Our favorite Day One Y Combinator startups
- All the Day Two Y Combinator startups
- Our favorite Day Two Y Combinator startups
Those entries should be pretty exhaustive, so dig into them when you can.
And make sure to read Natasha’s great piece on a super-hot startup from the batch, which comes up in the show. Peep that we are back on YouTube and we’ll be right back. Stay cool!
Equity drops every Monday at 7:00 a.m. PT and Friday at 6:00 a.m. PT, so subscribe to us on Apple Podcasts, Overcast, Spotify and all the casts.
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Our 12 favorite startups from Y Combinator’s S20 Demo Day: Part 2
Figma for filmmakers, TikTok for English learners and a cryptocurrency twist that actually makes sense?
After 197 pitches, Y Combinator’s Demo Day for its Summer 2020 cohort has concluded. While the fanfare, run-ins and fortune cookies were missing in this virtual session, it was still exciting to see and hear founders from 26 countries pitch their passions. Of course, some opted for a more quiet route, raising millions before the two-day pitch session even kicked off.
Members of the Summer 2020 class drew attention from nearly 2,400 investors across the world. For those who didn’t tune in, no worries: here’s our write-up of the companies that presented yesterday.
Participating startups spanned a number of sectors: we saw companies in the future of work, sustainability, no-code, consumer, edtech and delivery solutions. Several entrepreneurs aimed big at e-mail, small at socks and straight at Shopify’s recent success.
While TechCrunch reporters aren’t in the business of cutting checks or predicting success, read on to learn about the 12 startups that stuck out to us for a variety of reasons (apart from their Zoom backgrounds).
CarbonChain
CarbonChain may be the company that times the carbon market correctly. Now that the European Union and other regions are taking a serious look at penalizing businesses that fail to reduce carbon emissions, a service that provides accurate accounting for a company’s carbon footprint will be increasingly valuable.
And if the company can add marketplace and offsetting services on the back of its assessments, then its proposition becomes even more valuable. But what really makes CarbonChain stand out is the rigor with which it approaches its measurements.
The company uses independent software tools to make a digital twin of the carbon-emitting assets in a company’s business and claims that it can determine the emissions footprint of operations down to a cup of coffee (it also has models for the carbon footprint of heavy industrial equipment in the world’s most polluting industries).
For the world to address its carbon emissions, companies must understand their contribution to the problem. CarbonChain could be an invaluable tool in that effort.
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Our 11 favorite companies from Y Combinator’s S20 Demo Day: Part I
Startup incubator and investment group Y Combinator today held the first of two demo days for founders in its Summer 2020 batch.
So far, this cohort contains the usual mix of bold, impressive and, at times, slightly wacky ideas young companies so often show off.
This was Y Combinator’s second online demo day, its first all-virtual class and the first time that it held live, remote pitches. The event largely went well, with founders dialing in from around the globe to share a few paragraphs of notes and a single slide. There were few technical hiccups, given the sheer number of startups presenting.
But if you are not in the mood to parse through dozens (and dozens) of entries detailing each startup that showed off its problem, solution and growth, the TechCrunch crew has collected our own favorites based on how likely a company seems to succeed and how impressed we were with the creativity of their vision. For each entry, one staffer made the call that the startup in question was among their favorites.
We’re not investors, so we’re not pretending to sort the unicorns from the goats. But if what you need is a digest of some of the day’s best companies to get a good taste of what founders are building, we have your back.
ZipSchool and Hellosaurus
The next wave of edtech startups is entering a market that demands a better remote-learning solution for younger learners. But that’s the obvious product gap, one that is already being tackled by the biggest names in the booming category.
The non-obvious product-market deficit is how teachers, also impacted by the pandemic, are searching for new ways to interact with students. Teachers are collaborating and cross-pollinating on successful lesson plans that work across stale Zoom screens, so why not monetize that same content?
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