Oct
07
2020
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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.

Oct
05
2020
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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.

Sep
29
2020
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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.”

Sep
16
2020
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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.”

Sep
03
2020
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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.”

Jul
28
2020
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YC alum Paragon snags $2.5M seed for low-code app integration platform

Low-code is a hot category these days. It helps companies build workflows or simple applications without coding skills, freeing up valuable engineering resources for more important projects. Paragon, a member of the Y Combinator Winter 2020 cohort, announced a $2.5 million seed round today for its low-code application integration platform.

Investors include Y Combinator, Village Global, Global Founders Capital, Soma Capital and FundersClub.

“Paragon makes it easier for non-technical people to be able to build out integrations using our visual workflow editor. We essentially provide building blocks for things like API requests, interactions with third party APIs and conditional logic. And so users can drag and drop these building blocks to create workflows that describe business logic in their application,” says company co-founder Brandon Foo.

Foo acknowledges there are a lot of low-code workflow tools out there, but many like UIPath, Blue Prism and Automation Anywhere concentrate on robotic process automation (RPA) to automate certain tasks. He says he and co-founder Ishmael Samuel wanted to focus on developers.

“We’re really focused on how can we improve developer efficiency, and how can we bring the benefits of low code to product and engineering teams and make it easier to build products without writing manual code for every single integration, and really be able to streamline the product development process,” Foo told TechCrunch.

The way it works is you can drag and drop one of 1,200 predefined connectors for tools like Stripe, Slack and Google Drive into a workflow template, and build connectors very quickly to trigger some sort of action. The company is built on AWS serverless architecture, so you define the trigger action and subsequent actions, and Paragon handles all of the back-end infrastructure requirements for you.

It’s early days for the company. After launching in private beta in January, the company has 80 customers. It currently has six employees, including Foo, who previously co-founded Polymail, and Samuel, who was previously lead engineer at Uber. They plan to hire four more employees this year.

With both founders people of color, they definitely are looking to build a diverse team around them. “I think it’s already sort of built into our DNA. As a diverse founding team we have perhaps a broader viewpoint and perspective in terms of hiring the kind of people that we seek to work with. Of course, I think there’s always room for improvement, and so we’re always looking for new ways that we can be more inclusive in our hiring recruiting process [as we grow],” he said.

As far as raising during a pandemic, he says it’s been a crazy time, but he believes they are solving a real problem and that they can succeed in spite of the macro economic conditions of the moment.

Jul
22
2020
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Reflect wants to help you automate web testing without writing code

Reflect, a member of the Y Combinator Summer 2020 class, is building a tool to automate website and web application testing, making it faster to get your site up and running without waiting for engineers to write testing code, or for human testers to run the site through its paces.

Company CEO and co-founder Fitz Nowlan says his startup’s goal is to allow companies to have the ease of use and convenience of manual testing, but the speed of execution of automated or code-based testing.

“Reflect is a no-code tool for creating automated tests. Typically when you change your website, or your web application, you have to test it, and you have the choice of either having your engineers build coded tests to run through and ensure the correctness of your application, or you can hire human testers to do it manually,” he said.

With Reflect, you simply teach the tool how to test your site or application by running through it once, and based on those actions, Reflect can create a test suite for you. “You enter your URL, and we load it in a browser in a virtual machine in the cloud. From there, you just use your application just like a normal user would, and by using your application, you’re telling us what is important to test,” Nowlan explained.

He adds, “Reflect will observe all of your actions throughout that whole interaction with that whole browser session. And then from those actions, it will distill that down into a repeatable machine executable test.”

Nowlan and co-founder Todd McNeal started the company in September 2019 after spending five years together at a digital marketing startup near Philadelphia, where they experienced problems with web testing first-hand.

They launched a free version of this product in April, just as we were beginning to feel the full force of the pandemic in the U.S, a point that was not lost on him. “We didn’t want to delay any longer and we just felt like, you know you got to get up there and swing the bat,” he said.

Today, the company has 20 paying customers, and he has found that the pandemic has helped speed up sales in some instances, while slowing it down in others.

He says the remote YC experience has been a positive one, and in fact he couldn’t have participated had they had to show up in California as they have families and homes in Pennsylvania.  He says that the remote nature of the current program forces you to be fully engaged mentally to get the most out of the program.

“It’s just a little more mental work to prepare yourself and to have the mental energy to stay locked in for a remote batch. But I think if you can get over that initial hump, the information flow and the knowledge sharing is all the same,” he said.

He says as technical founders, the program has helped them focus on the sales and marketing side of the equation, and taught them that it’s more than building a good product. You still have to go out there and sell it to build a company.

He says his short-term goal is to get as many people as he can using the platform, which will help them refine their ability to automate the test building. For starters, that involves recording activities on-screen, but over time they plan to layer on machine learning and that requires more data.

“We’re going to focus primarily over the next six to 12 months on growing our customer base — both paid and unpaid — and I really mean that we want people to come in and create tests. Even if they [use the free product], we’re benefiting from that creation of that test,” he said.

Jul
14
2020
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Recurrency is taking on giants like SAP with a modern twist on ERP

Recurrency, a member of the Summer 2020 Y Combinator cohort, was started by a 21 year old just out of college. He decided to take on a highly established market that is led by giants like SAP, Infor, Oracle and Microsoft, but instead of taking a highly complex area of enterprise software in one big bite, he is starting by helping wholesale businesses.

Sole founder and company CEO Sam Oshay just graduated from the University of Pennsylvania with a dual degree that straddled engineering and business, before joining the summer batch. Oshay is bringing a modern twist to ERP by using machine learning to drive more data-driven decision making.

“What makes us different from other ERPs like SAP, Infor and Epicor is that we can tell the user something that they don’t already know.” He says these traditional ERPs are basically data entry systems. For example, you could enter a pricing list, but you can’t do anything with it in terms of predictions.

“We can scan historical data and make pricing recommendations and predictions. So we are an ERP that not only does data analysis, but also imports external data and matches it to internal data to make recommendations and predictions,” Oshay explained.

While he doesn’t expect to remain confined to just the wholesale side of the business, it makes sense that he started with it because his family has a history of running these kinds of businesses. In fact, his grandfather immigrated to the U.S. after World War II and started a hardware wholesale business that his uncle still runs today. His dad started his own business selling wholesale shipping supplies, and he grew up in the family business, giving him some insight that most recent college grads probably wouldn’t have.

“I learned about the wholesale business at a very deep level. And what I observed is that so many of the issues with my dad’s business came down to issues with his ERP system. It occurred to me that if someone were to build an ERP extension or a better ERP, they could unlock so much of the value that is currently locked inside these legacy systems,” he said.

So he did what good entrepreneurs do, and began building it. For starters, his system plugs into legacy systems like SAP or NetSuite, but the plan is to build a better ERP, one step at a time. For now, it’s about wholesale, but he has a much broader vision for his company.

He originally applied to YC during the Fall 2019 semester of his junior year, and was admitted to the winter batch, but deferred to the Summer 2020 group to complete his studies. He spent his remaining time at UPenn sprinting to early graduation, taking 10 classes to come close to finishing his studies (with just a dissertation standing between him and his degree).

With this batch being delivered remotely, he says that the YC team has taken that into account and is still offering a meaningful experience for the summer group. “All of the events that YC would normally be doing are still happening, just remotely. And to my knowledge, some of the events we’re doing are designed specifically for this weird set of circumstances. The YC team has put quite a bit of thought into making this batch meaningful and I think they’ve succeeded,” he said.

While the pandemic has created new challenges for an early-stage business, he says that in some ways it’s helped him focus better. Instead of going out with friends, he’s home with his head down working on his company with little distraction.

As you would expect, it’s early days for the product, but he has three customers who are operational and two more in the implementation phase. He also has two employees so far, a front end and back end engineer.

For now, he’s going to continue building his product and his business, and he sees the pandemic as a time when businesses might be more open to changing a system like a legacy ERP. “If they want to try something new, and you can make it easier for them to try that, I’ve found that’s a place where you can make a sale,” he said.

Jul
02
2020
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QuestDB nabs $2.3M seed to build open source time series database

QuestDB, a member of the Y Combinator summer 2020 cohort, is building an open source time series database with speed top of mind. Today the startup announced a $2.3 million seed round.

Episode1 Ventures led the round with assistance from Seedcamp, 7percent Ventures, YCombinator, Kima Ventures and several unnamed angel investors.

The database was originally conceived in 2013 when current CTO Vlad Ilyushchenko was building trading systems for a financial services company and he was frustrated by the performance limitations of the databases available at the time, so he began building a database that could handle large amounts of data and process it extremely fast.

For a number of years, QuestDB was a side project, a labor of love for Ilyushchenko until he met his other co-founders Nicolas Hourcard, who became CEO and Tancrede Collard, who became CPO, and the three decided to build a startup on top of the open source project last year.

“We’re building an open source database for time series data, and time series databases are a multi-billion-dollar market because they’re central for financial services, IoT and other enterprise applications. And we basically make it easy to handle explosive amounts of data, and to reduce infrastructure costs massively,” Hourcard told TechCrunch.

He adds that it’s also about high performance. “We recently released a demo that you can access from our website that enables you to query a super large datasets — 1.6 billion rows with sub-second queries, mostly, and that just illustrates how performant the software is,” he said.

He sees open source as a way to build adoption from the bottom up inside organizations, winning the hearts and minds of developers first, then moving deeper in the company when they eventually build a managed cloud version of the product. For now, being open source also helps them as a small team to have a community of contributors help build the database and add to its feature set.

“We’ve got this open source product that is free to use, and it’s pretty important for us to have such a distribution model because we can basically empower developers to solve their problems, and we can ask for contributions from various communities. […] And this is really a way to spur adoption,” Hourcard said.

He says that working with YC has allowed them to talk to other companies in the ecosystem who have built similar open source-based startups and that’s been helpful, but it has also helped them learn to set and meet goals and have access to some of the biggest names in Silicon Valley, including Marc Andreessen, who delivered a talk to the cohort the same day we spoke.

Today the company has seven employees, including the three founders, spread out across the US, EU and South America. He sees this geographic diversity helping when it comes to building a diverse team in the future. “We definitely want to have more diverse backgrounds to make sure that we keep having a diverse team and we’re very strongly committed to that.”

For the short term, the company wants to continue building its community, working on continuing to improve the open source product, while working on the managed cloud product.

May
18
2020
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GO1, an enterprise learning platform, picks up $40M from Microsoft, Salesforce and more

With a large proportion of knowledge workers doing now doing their jobs from home, the need for tools to help them feel connected to their profession can be as important as tools to, more practically, keep them connected. Today, a company that helps do precisely that is announcing a growth round of funding after seeing engagement on its platform triple in the last month.

GO1.com, an online learning platform focused specifically on professional training courses (both those to enhance a worker’s skills as well as those needed for company compliance training), is today announcing that it has raised $40 million in funding, a Series C that it plans to use to continue expanding its business. The startup was founded in Brisbane, Australia and now has operations also based out of San Francisco — it was part of a Y Combinator cohort back in 2015 — and more specifically, it wants to continue growth in North America, and to continue expanding its partner network.

GO1 not disclosing its valuation but we are asking. It’s worth pointing out that not only has it seen engagement triple in the last month as companies turn to online learning to keep users connected to their professional lives even as they work among children and house pets, noisy neighbours, dirty laundry, sourdough starters, and the rest (and that’s before you count the harrowing health news we are hit with on a regular basis). But even beyond that, longer term GO1 has shown some strong signs that speak of its traction.

It counts the likes of the University of Oxford, Suzuki, Asahi and Thrifty among its 3,000+ customers, with more than 1.5 million users overall able to access over 170,000 courses and other resources provided by some 100 vetted content partners. Overall usage has grown five-fold over the last 12 months. (GO1 works both with in-house learning management systems or provides its own.)

“GO1’s growth over the last couple of months has been unprecedented and the use of online tools for training is now undergoing a structural shift,” said Andrew Barnes, CEO of GO1, in a statement. “It is gratifying to fill an important void right now as workers embrace online solutions. We are inspired about the future that we are building as we expand our platform with new mediums that reach millions of people every day with the content they need.”

The funding is coming from a very strong list of backers: it’s being co-led by Madrona Venture Group and SEEK — the online recruitment and course directory company that has backed a number of edtech startups, including FutureLearn and Coursera — with participation also from Microsoft’s venture arm M12; new backer Salesforce Ventures, the investing arm of the CRM giant; and another previous backer, Our Innovation Fund.

Microsoft is a strategic backer: GO1 integrated with Teams, so now users can access GO1 content directly via Microsoft’s enterprise-facing video and messaging platform.

“GO1 has been critical for business continuity as organizations navigate the remote realities of COVID-19,” said Nagraj Kashyap, Microsoft Corporate Vice President and Global Head of M12, in a statement. “The GO1 integration with Microsoft Teams offers a seamless learning experience at a time when 75 million people are using the application daily. We’re proud to invest in a solution helping keep employees learning and businesses growing through this time.”

Similarly, Salesforce is also coming in as a strategic, integrating this into its own online personal development products and initiatives.

“We are excited about partnering with GO1 as it looks to scale its online content hub globally. While the majority of corporate learning is done in person today, we believe the new digital imperative will see an acceleration in the shift to online learning tools. We believe GO1 fits well into the Trailhead ecosystem and our vision of creating the life-long learner journey,” said Rob Keith, Head of Australia, Salesforce Ventures, in a statement.

Working remotely has raised a whole new set of challenges for organizations, especially those whose employees typically have never before worked for days, weeks and months outside of the office.

Some of these have been challenges of a more basic IT nature: getting secure access to systems on the right kinds of machines and making sure people can communicate in the ways that they need to to get work done.

But others are more nuanced and long-term but actually just as important, such as making sure people remain in a healthy state of mind about work. Education is one way of getting them on the right track: professional development is not only useful for the person to do her or his job better, but it’s a way to motivate people, to focus their minds, and take a rest from their routines, but in a way that still remains relevant to work.

GO1 is absolutely not the only company pursuing this opportunity. Others include Udemy and Coursera, which have both come to enterprise after initially focusing more on traditional education plays. And LinkedIn Learning (which used to be known as Lynda, before LinkedIn acquired it and shifted the branding) was a trailblazer in this space.

For these, enterprise training sits in a different strategic place to GO1, which started out with compliance training and onboarding of employees before gravitating into a much wider set of topics that range from photography and design, through to Java, accounting, and even yoga and mindfulness training and everything in between.

It’s perhaps the directional approach, alongside its success, that have set GO1 apart from the competition and that has attracted the investment, which seems to have come ahead even of the current boost in usage.

“We met GO1 many months before COVID-19 was on the tip of everyone’s tongue and were impressed then with the growth of the platform and the ability of the team to expand their corporate training offering significantly in North America and Europe,” commented S. Somasegar, managing director, Madrona Venture Group, in a statement. “The global pandemic has only increased the need to both provide training and retraining – and also to do it remotely. GO1 is an important link in the chain of recovery.” As part of the funding Somasegar will join the GO1 board of directors.

Notably, GO1 is currently making all COVID-19 related learning resources available for free “to help teams continue to perform and feel supported during this time of disruption and change,” the company said.

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