Dec
15
2020
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Parsec raises $25M from a16z to power remote work and cloud gaming

Parsec, a startup that’s built streaming technology for both work and play, is announcing that it has raised $25 million in Series B funding.

This brings Parsec’s total funding to $33 million, according to Crunchbase. The round was led by Andreessen Horowitz, with the firm’s general partner Martin Casado joining the board. Previous investors Lerer Hippeau, Makers Fund, NextView Ventures and Notation Capital also participated.

CEO Benjy Boxer told me that since he and CTO Chris Dickson founded the company in 2016, the vision has always been “to make it easier for people to connect to their technology, software and content from anywhere, on any device.”

They started out by helping gamers access their gaming PCs from other devices (the Parsec app is currently available for Windows, Mac, Linux, Android, Raspberry Pi and the web).

“From the beginning, we thought that if we could build something that is great for gaming, it will be great for everything,” Boxer said.

But it was a natural transition to other use cases, since some of the people using Parsec to play games in their free time also turned out to work at TV production companies, video game companies or in other jobs where they need access to high-end workstations. That’s why the company launched Parsec for Teams this year, which offers the same low-latency remote experience, while also adding features like encryption, group permissions and collaboration on the same file.

Parsec screenshot

Image Credits: Parsec

“The performance of Parsec is just way above everything else,” Boxer said. “People forget they’re using Parsec.”

Parsec works with major gaming clients like EA, Ubisoft, Blizzard Entertainment and Square Enix, and it’s also being used in industries like architecture, engineering and video broadcast/production/post-production.

And as you might imagine, the need for something like this has only increased during the pandemic. Boxer said customers have found that the platform is saving their employees more than an hour a day by eliminating the commute and giving them high-speed access to their workstations — rather than, say, having to wait an hour for a 100 gigabyte file to download.

And most of those clients anticipate that after the pandemic, their employees will continue for work from home for part of the time.

“So in that scenario, people are bringing their computers back to the office, and they can use Parsec to make sure it’s always accessible to them,” Boxer said.

On the consumer side, he said that where usage was previously heaviest during the weekends, during the pandemic “there’s no spike anymore on the weekends, people are playing all the time.”

Boxer added that the company will continue developing the core platform, leading to improvements for both gaming and enterprise users, while there’s a separate team focused on building administrative and collaborative features.

 

Dec
07
2020
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Tecton.ai nabs $35M Series B as it releases machine learning feature store

Tecton.ai, the startup founded by three former Uber engineers who wanted to bring the machine learning feature store idea to the masses, announced a $35 million Series B today, just seven months after announcing their $20 million Series A.

When we spoke to the company in April, it was working with early customers in a beta version of the product, but today, in addition to the funding, they are also announcing the general availability of the platform.

As with their Series A, this round has Andreessen Horowitz and Sequoia Capital co-leading the investment. The company has now raised $60 million.

The reason these two firms are so committed to Tecton is the specific problem around machine learning the company is trying to solve. “We help organizations put machine learning into production. That’s the whole goal of our company, helping someone build an operational machine learning application, meaning an application that’s powering their fraud system or something real for them […] and making it easy for them to build and deploy and maintain,” company CEO and co-founder Mike Del Balso explained.

They do this by providing the concept of a feature store, an idea they came up with and which is becoming a machine learning category unto itself. Just last week, AWS announced the Sagemaker Feature store, which the company saw as major validation of their idea.

As Tecton defines it, a feature store is an end-to-end machine learning management system that includes the pipelines to transform the data into what are called feature values, then it stores and manages all of that feature data and finally it serves a consistent set of data.

Del Balso says this works hand-in-hand with the other layers of a machine learning stack. “When you build a machine learning application, you use a machine learning stack that could include a model training system, maybe a model serving system or an MLOps kind of layer that does all the model management, and then you have a feature management layer, a feature store which is us — and so we’re an end-to-end life cycle for the data pipelines,” he said.

With so much money behind the company it is growing fast, going from 17 employees to 26 since we spoke in April, with plans to more than double that number by the end of next year. Del Balso says he and his co-founders are committed to building a diverse and inclusive company, but he acknowledges it’s not easy to do.

“It’s actually something that we have a primary recruiting initiative on. It’s very hard, and it takes a lot of effort, it’s not something that you can just make like a second priority and not take it seriously,” he said. To that end, the company has sponsored and attended diversity hiring conferences and has focused its recruiting efforts on finding a diverse set of candidates, he said.

Unlike a lot of startups we’ve spoken to, Del Balso wants to return to an office setup as soon as it is feasible to do so, seeing it as a way to build more personal connections between employees.

Nov
11
2020
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Fishtown Analytics raises $29.5M Series B for its data engineering platform

Fishtown Analytics, the Philadelphia-based company behind the dbt open-source data engineering tool, today announced that it has raised a $29.5 million Series B round led by Sequoia Capital, with participation from previous investors Andreessen Horowitz and Amplify Partners.

The company is building a platform that allows data analysts to more easily create and disseminate organizational knowledge. Its focus is on data modeling, with its dbt tool allowing anybody who knows SQL to build data transformation workflows. Dbt also features support for automatically testing data quality and documenting changes, but maybe most importantly it uses standard software engineering techniques to help engineers collaborate on code and integrate changes continuously.

If this all sounds a bit familiar, it’s probably because you saw that Fishtown Analytics also announced a $12.9 million Series A round in April. It’s not often we see both a Series A and B round within half a year, but that goes to show how the market for Fishtown’s service is expanding as companies continue to grapple with how to best make use of their data — and how much investors want to be part of that. 

Image Credits: Fishtown

“This was a very productive thing for us,” Fishtown Analytics co-founder and CEO Tristan Handy told me when I asked him why he raised again so quickly. “It’s standard best practice to do quarterly catch-ups with investors and eventually you’ll be ready to fundraise. And Matt Miller from Sequoia showed up to one of these quarterly catch-ups and he shared the 40-page memo that he had written to the Sequoia partnership — and he came with the term sheet.”

Initially, Handy declined. “We’re very bullheaded people, I think, as many founders are. It took some real reflection and thinking about, ‘is this what we want to be doing right now?’ ”

In the end, though, the team decided to go ahead with this round — mostly because this round allowed the team to think long-term and provided stability and certainty.

One thing Handy has always been very clear about is that he did not found Fishtown to purely build the largest possible company but to solve its users’ problems, even as the market looked at companies like Databricks and Snowflake — and their financial success — as potential analogs. “My worry was that the financial markets were driving things that weren’t necessarily going to be good for our users,” Handy said.

Jun
30
2020
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Fivetran snares $100M Series C on $1.2B valuation for data connectivity solution

A big problem for companies these days is finding ways to connect various data sources to their data repositories, and Fivetran is a startup with a solution to solve that very problem. No surprise then that even during a pandemic, the company announced today that it has raised a $100 million Series C on a $1.2 billion valuation.

The company didn’t mess around, with top flight firms Andreessen Horowitz and General Catalyst leading the investment, with participation from existing investors CEAS Investments and Matrix Partners. Today’s money brings the total raised so far to $163 million, according to the company.

Martin Casado from a16z described the company succinctly in a blog post he wrote after its $44 million Series B in September 2019, in which his firm also participated. “Fivetran is a SaaS service that connects to the critical data sources in an organization, pulls and processes all the data, and then dumps it into a warehouse (e.g., Snowflake, BigQuery or RedShift) for SQL access and further transformations, if needed. If data is the new oil, then Fivetran is the pipes that get it from the source to the refinery,” he wrote.

Writing in a blog post today announcing the new funding, CEO George Fraser added that in spite of current conditions, the company has continued to add customers. “Despite recent economic uncertainty, Fivetran has continued to grow rapidly as customers see the opportunity to reduce their total cost of ownership by adopting our product in place of highly customized, in-house ETL pipelines that require constant maintenance,” he wrote.

In fact, the company reports 75% customer growth over the prior 12 months. It now has more than 1,100 customers, which is a pretty good benchmark for a Series C company. Customers include Databricks, DocuSign, Forever 21, Square, Udacity and Urban Outfitters, crossing a variety of verticals.

Fivetran hopes to continue to build new data connectors as it expands the reach of its product and to push into new markets, even in the midst of today’s economic climate. With $100 million in the bank, it should have enough runway to ride this out, while expanding where it makes sense.

May
27
2020
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Census raises $4.3M seed to put product info in cloud data warehouses to work

Companies spend inordinate amounts of time and money building data warehouses and moving data from enterprise applications. But once they get the data in, how do they get specific information like product data back out and distribute it to business operations, which can use it to better understand customers? That’s where Census comes in. It builds a layer on top of the data warehouse that makes it easy for the data team to distribute product data where it’s needed.

The company announced a $4.3 million seed today, although it closed last year while they were still building the product. That round was led by Andreessen Horowitz with help from SV Angel and a number of angel investors.

Census CEO Boris Jabes says the company was founded to solve this problem of data distribution from a cloud data warehouse. He says for starters they are concentrating on product data.

“The product is designed to sync data directly from cloud data warehouses like Snowflake, BigQuery and Redshift […] and the main reason we did that was people really needed to get access to this kind of product data and all this data that’s locked in all their systems and take advantage of it,” Jabes explained.

He says that the first step is to make the product data sitting in the data warehouse actionable for the organization. They are working with data teams at early customers to remove the complexity of getting that data out of the warehouse and putting it to work in a more automated fashion.

They do this by creating a unified schema that sits on top of the data in the warehouse and makes it easier to distribute it to the teams that need it inside the organization. It essentially acts as a middleware layer on top of the warehouse that you can take advantage of without having to write code to decide where data might be most useful.

David Ulevitch, who led the investment at a16z, says that removing this manual part of the process is highly valuable. “For years, organizations have had to do the frustrating task of manually syncing data between dozens of apps. This friction is especially painful now that data has become critical to every team in a business, from product to sales. Census sets a new standard for how product-led SaaS companies can operationalize data,” he said in a statement.

Jabes understands these are difficult times for every business, and especially an early-stage startup, but he says they are focusing on an aspect of the business that potential customers need.

“We’ve seen companies actually spending time trying to tackle some of these data problems […] so I’m still optimistic,” he says.

May
07
2020
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VC’s largest funds make big bets on vertical B2B marketplaces

During the waning days of the first dot-com boom, some of the biggest names in venture capital invested in marketplaces and directories whose sole function was to consolidate information and foster transparency in industries that had remained opaque for decades.

The thesis was that thousands of small businesses were making specialized products consumed by larger businesses in huge industries, but the reach of smaller players was limited by their dependence on a sales structure built on conferences and personal interactions.

Companies making pharmaceuticals, chemicals, construction materials and medical supplies represented trillions in sales, but those huge aggregate numbers hide how fragmented these supply chains are — and how difficult it is for buyers to see the breadth of sellers available.

Now, similar to the way business models popularized by Kozmo.com and Webvan in decades past have since been reincarnated as Postmates and DoorDash, the B2B directory and marketplace rises from the investment graveyard.

The first sign of life for the directory model came with the success of GoodRX back in 2011. The company proved that when information about pricing in a previously opaque industry becomes available, it can unleash a torrent of new demand.

Apr
30
2020
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Figma raises $50 million Series D led by Andreessen Horowitz

Figma, the design platform that lets folks work collaboratively and in the cloud, has today announced the close of a $50 million Series D financing. The round was led by Andreessen Horowitz, with partner Peter Levine and cofounding partner Marc Andreessen managing the deal for the firm. New angel investors, including Henry Ellenbogen from Durable Capital, also participated in the round alongside existing investors Index, Greylock, KPCB, Sequoia and Founders Fund.

Forbes reports that the latest funding round values Figma at $2 billion.

Dylan Field, Figma founder and CEO, told TechCrunch that discussions between a16z and Figma actually began towards the end of the fundraising cycle for the company’s Series C, which closed in February of 2019.

“It felt a bit like a shotgun wedding,” said Field, explaining that both parties instead opted to get to know each other better. They’ve been building their relationship over the past year, leading to today’s Series D close. Field also added that he has not met other investors in this round in person, and the vast majority of the deal was done over Zoom.

“When you think about the future of Silicon Valley, there is an interesting question around capital infrastructure being here and people not being able to access that if they’re not here, too,” said Field. “I got to see firsthand how a deal done online can work and I think more and more investors aren’t going to worry about whether you’re in Silicon Valley or not.”

Figma launched in 2015 after nearly six years of development in stealth. The premise was to create a collaborative, cloud-based design tool that would be the Google Docs of design.

Since, Figma has built out the platform to expand access and usability for individual designers, small firms and giant enterprise companies alike. For example, the company launched plug-ins in 2019, allowing developers to build in their own tools to the app, such as a plug-in for designers to automatically rename and organize their layers as they work (Rename.it) and one that gives users the ability to add placeholder text that they can automatically find and replace later (Content Buddy).

The company also launched an educational platform called Community, which gives designers the ability to share their work and let other users ‘remix’ that design, or simply check out how it was built, layer by layer.

A spokesperson told TechCrunch that this deal was “opportunistic,” and that the company was in a strong cash position pre-financing. The new funding expands Figma’s runway during these uncertain times, with coronavirus halting a lot of enterprise purchasing and ultimately slowing growth of some rising enterprise players.

Field explained that Figma’s data is counter to the expected narrative around enterprise purchasing because Figma is specifically built to let teams collaborate in the cloud.

“We’re actually seeing a lot of acceleration for bigger deals on the sales side,” said Field. “Figma is a tool that can help right now.”

The company says that one interesting change they’ve seen in the COVID era is a significant jump in user engagement from teams to collaborate more in Figma. The firm has also seen an uptick in whiteboarding, note taking, slide deck creation and diagramming, as companies start using Figma as a collaborative tool across an entire organization rather than just within a team of designers.

This latest deal brings Figma’s total funding to $132.9 million. Field added that, though the company is not yet profitable, this latest financing gives the company three to four years of runway, even with aggressive scaling and hiring efforts moving forward.

Apr
28
2020
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Tecton.ai emerges from stealth with $20M Series A to build machine learning platform

Three former Uber engineers, who helped build the company’s Michelangelo machine learning platform, left the company last year to form Tecton.ai and build an operational machine learning platform for everyone else. Today the company announced a $20 million Series A from a couple of high-profile investors.

Andreessen Horowitz and Sequoia Capital co-led the round with Martin Casado, general partner at a16z and Matt Miller, partner at Sequoia joining the company board under the terms of the agreement. Today’s investment combined with the seed they used to spend the last year building the product comes to $25 million. Not bad in today’s environment.

But when you have the pedigree of these three founders — CEO Mike Del Balso, CTO Kevin Stumpf and VP of Engineering Jeremy Hermann all helped build the Uber system —  investors will spend some money, especially when you are trying to solve a difficult problem around machine learning.

The Michelangelo system was the machine learning platform at Uber that looked at things like driver safety, estimated arrival time and fraud detection, among other things. The three founders wanted to take what they had learned at Uber and put it to work for companies struggling with machine learning.

“What Tecton is really about is helping organizations make it really easy to build production-level machine learning systems, and put them in production and operate them correctly. And we focus on the data layer of machine learning,” CEO Del Balso told TechCrunch.

Image Credit: Tecton.ai

Del Balso says part of the problem, even for companies that are machine learning-savvy, is building and reusing models across different use cases. In fact, he says the vast majority of machine learning projects out there are failing, and Tecton wanted to give these companies the tools to change that.

The company has come up with a solution to make it much easier to create a model and put it to work by connecting to data sources, making it easier to reuse the data and the models across related use cases. “We’re focused on the data tasks related to machine learning, and all the data pipelines that are related to power those models,” Del Balso said.

Certainly Martin Casado from a16z sees a problem in search of a solution and he likes the background of this team and its understanding of building a system like this at scale. “After tracking a number of deep engagements with top ML teams and their interest in what Tecton was building, we invested in Tecton’s A alongside Sequoia. We strongly believe that these systems will continue to increasingly rely on data and ML models, and an entirely new tool chain is needed to aid in developing them…,” he wrote in a blog post announcing the funding.

The company currently has 17 employees and is looking to hire, particularly data scientists and machine learning engineers, with a goal of 30 employees by the end of the year.

While Del Balso is certainly cognizant of the current economic situation, he believes he can still build this company because he’s solving a problem that people genuinely are looking for help with right now around machine learning.

“From the customers we’re talking to, they need to solve these problems, and so we don’t see things slowing down,” he said.

Apr
22
2020
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Fishtown Analytics raises $12.9M Series A for its open-source analytics engineering tool

Philadelphia-based Fishtown Analytics, the company behind the popular open-source data engineering tool dbt, today announced that it has raised a $12.9 million Series A round led by Andreessen Horowitz, with the firm’s general partner Martin Casado joining the company’s board.

“I wrote this blog post in early 2016, essentially saying that analysts needed to work in a fundamentally different way,” Fishtown founder and CEO Tristan Handy told me, when I asked him about how the product came to be. “They needed to work in a way that much more closely mirrored the way the software engineers work and software engineers have been figuring this shit out for years and data analysts are still like sending each other Microsoft Excel docs over email.”

The dbt open-source project forms the basis of this. It allows anyone who can write SQL queries to transform data and then load it into their preferred analytics tools. As such, it sits in-between data warehouses and the tools that load data into them on one end, and specialized analytics tools on the other.

As Casado noted when I talked to him about the investment, data warehouses have now made it affordable for businesses to store all of their data before it is transformed. So what was traditionally “extract, transform, load” (ETL) has now become “extract, load, transform” (ELT). Andreessen Horowitz is already invested in Fivetran, which helps businesses move their data into their warehouses, so it makes sense for the firm to also tackle the other side of this business.

“Dbt is, as far as we can tell, the leading community for transformation and it’s a company we’ve been tracking for at least a year,” Casado said. He also argued that data analysts — unlike data scientists — are not really catered to as a group.

Before this round, Fishtown hadn’t raised a lot of money, even though it has been around for a few years now, except for a small SAFE round from Amplify.

But Handy argued that the company needed this time to prove that it was on to something and build a community. That community now consists of more than 1,700 companies that use the dbt project in some form and over 5,000 people in the dbt Slack community. Fishtown also now has over 250 dbt Cloud customers and the company signed up a number of big enterprise clients earlier this year. With that, the company needed to raise money to expand and also better service its current list of customers.

“We live in Philadelphia. The cost of living is low here and none of us really care to make a quadro-billion dollars, but we do want to answer the question of how do we best serve the community,” Handy said. “And for the first time, in the early part of the year, we were like, holy shit, we can’t keep up with all of the stuff that people need from us.”

The company plans to expand the team from 25 to 50 employees in 2020 and with those, the team plans to improve and expand the product, especially its IDE for data analysts, which Handy admitted could use a bit more polish.

Mar
03
2020
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$75M legal startup Atrium shuts down, lays off 100

Justin Kan’s hybrid legal software and law firm startup Atrium is shutting down today after failing to figure out how to deliver better efficiency than a traditional law firm, the CEO tells TechCrunch exclusively. The startup has now laid off all its employees, which totaled just over 100. It will return some of its $75.5 million in funding to investors, including Series B lead Andreessen Horowitz. The separate Atrium law firm will continue to operate.

“I’m really grateful to the customers and the team members who came along with me and our investors. It’s unfortunate that this wasn’t the outcome that we wanted but we’re thankful to everyone that came with us on the journey,” said Kan. He’d previously founded Justin.tv, which pivoted to become Twitch and later sold to Amazon for $970 million. “We decided to call it and wind down the startup operations. There will be some capital returned to investors post wind-down,” Kan told me.

Atrium had attempted a pivot back in January, laying off its in-house lawyers to become a more pure software startup with better margins. Some of its lawyers formed a separate standalone legal firm and took on former Atrium clients. But Kan tells me that it was tough to regain momentum coming out of that change, which some Atrium customers tell me felt chaotic and left them unsure of their legal representation.

More layoffs quietly ensued as divisions connected to those lawyers were eliminated. But trying to build software for third-party lawyers, many of whom have entrenched processes and older leadership, proved difficult. The streamlined workflows may not have seemed worth the thrash of adopting new technology.

“If you look at our original business model with the verticalized law firm, a lot of these companies that have this kind of full stack model are not going to survive,” Kan explained. “A lot of these companies, Atrium included, did not figure out how to make a dent in operational efficiency.”

Disrupting law firms proves difficult

Founded in 2017, Atrium built software for startups to navigate fundraising, hiring, acquisition deals and collaboration with their legal team. Atrium also offered in-house lawyers that could provide counsel and best practices in these matters. The idea was that the collaboration software would make its lawyers more efficient than a traditional law firm so they could get work done faster, translating to savings for clients and Atrium.

Atrium’s software included Records, a Dropbox-esque system for keeping track of legal documents, and Hiring, which instantly generated employment offer letters based on details punched into a form while keeping track of signatures. The startup hoped it could prevent clients and lawyers from wasting time digging through email chains or missing a sign-off that could put them in legal jeopardy.

The company tried to generate client leads by hosting fundraising workshops for startups, starring Kan and his stories from growing Twitch. A charismatic leader with a near-billion-dollar exit under his belt, investors and founders alike were quick to buy into Kan’s vision and advice. Startups saw Atrium as an ally with industry expertise that could help them avoid dirty term sheets or botched hires.

But keeping a large squad of lawyers on staff proved costly. Atrium priced packages of its software and legal assistance under subscriptions, with momentous deals like acquisitions incurring add-on fees. The model relied less on milking clients with steep hourly rates measured down to six-minute increments like most law firms.

Yet eliminating the busywork for lawyers through its software didn’t materialize into bountiful profits. The pivot sought to create a professional services network where Atrium could route clients to attorneys. The layoffs had shaken faith in the startup as clients demanded stability, lest they be caught without counsel at a tough time.

Rather than trudge on, Kan decided to fold the company. The standalone Atrium law firm will continue to operate under partners Michel Narganes and Matthew Melville, but the startup developing legal software is done.

Atrium’s implosion could send ripples through the legal tech scene, and push other entrepreneurs to start with a more focused software-only approach.

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