The influence of a founder on their company’s culture cannot be overstated. Everything from their views on the product and business to how they think about people affects how their company’s employees will behave, and since behavior in turn informs culture, the consequences of a founder’s early decisions can be far-reaching.

So it’s not very surprising that Expensify has its own take on almost everything it does when you consider what its founder and CEO David Barrett learned early in his life: “Basically everyone is wrong about basically everything.” As we saw in part 1 of this EC-1, this led him to the revelation that it’s easier to figure things out for yourself than finding advice that applies to you. Eventually, these insights — and the adventurous P2P hacker attitude he nurtured alongside his colleagues and Travis Kalanick at Red Swoosh — would inform how he would go about shaping Expensify.

It’s striking how Expensify has managed to maintain this character 13 years later, even on the threshold of an IPO. How did this happen? During a series of interviews in February and early March, we found the answer is tied to the level of thought and effort this expense management business puts into its culture.

You see, the people at Expensify are prepared to invent their own playbook, develop it and, if needed, rewrite it completely. Its HR policies and strategy are tailored to find people who would have fun building an expense management product. It has a unique growth and recognition scheme to offset the drawbacks of a flat organizational structure. It’s even got a “Senate” that vets all major decisions. No kidding.

All this, and more, has ultimately helped Expensify reach more than 10 million users and achieve $100 million in annual revenue with just 130 employees. Let’s take a closer look at how Expensify makes it happen.

“We want the fewest people necessary to get the job done”

It’s clear Expensify’s unusually high employee-to-revenue ratio is intentional: “We want the fewest people necessary to get the job done,” Barrett says. But how do you actually achieve it? How do you hire and keep people who can deliver such results? Barrett had to learn how the hard way.

Expensify’s first team was based in San Francisco and comprised Barrett’s old Red Swoosh and Akamai colleagues, who joined a few months after Akamai fired him. A small team was enough to get started, but it was much more difficult to hire additional people. Barrett is eager to clarify the Valley is not really the best place to recruit talent: “Sure, Silicon Valley has a ton of really awesome people, but all of them have jobs!,” he says.

At Google I/O today Google Cloud announced Vertex AI, a new managed machine learning platform that is meant to make it easier for developers to deploy and maintain their AI models. It’s a bit of an odd announcement at I/O, which tends to focus on mobile and web developers and doesn’t traditionally feature a lot of Google Cloud news, but the fact that Google decided to announce Vertex today goes to show how important it thinks this new service is for a wide range of developers.

The launch of Vertex is the result of quite a bit of introspection by the Google Cloud team. “Machine learning in the enterprise is in crisis, in my view,” Craig Wiley, the director of product management for Google Cloud’s AI Platform, told me. “As someone who has worked in that space for a number of years, if you look at the Harvard Business Review or analyst reviews, or what have you — every single one of them comes out saying that the vast majority of companies are either investing or are interested in investing in machine learning and are not getting value from it. That has to change. It has to change.”

Wiley, who was also the general manager of AWS’s SageMaker AI service from 2016 to 2018 before coming to Google in 2019, noted that Google and others who were able to make machine learning work for themselves saw how it can have a transformational impact, but he also noted that the way the big clouds started offering these services was by launching dozens of services, “many of which were dead ends,” according to him (including some of Google’s own). “Ultimately, our goal with Vertex is to reduce the time to ROI for these enterprises, to make sure that they can not just build a model but get real value from the models they’re building.”

Vertex then is meant to be a very flexible platform that allows developers and data scientist across skill levels to quickly train models. Google says it takes about 80% fewer lines of code to train a model versus some of its competitors, for example, and then help them manage the entire lifecycle of these models.

The service is also integrated with Vizier, Google’s AI optimizer that can automatically tune hyperparameters in machine learning models. This greatly reduces the time it takes to tune a model and allows engineers to run more experiments and do so faster.

Vertex also offers a “Feature Store” that helps its users serve, share and reuse the machine learning features and Vertex Experiments to help them accelerate the deployment of their models into producing with faster model selection.

Deployment is backed by a continuous monitoring service and Vertex Pipelines, a rebrand of Google Cloud’s AI Platform Pipelines that helps teams manage the workflows involved in preparing and analyzing data for the models, train them, evaluate them and deploy them to production.

To give a wide variety of developers the right entry points, the service provides three interfaces: a drag-and-drop tool, notebooks for advanced users and — and this may be a bit of a surprise — BigQuery ML, Google’s tool for using standard SQL queries to create and execute machine learning models in its BigQuery data warehouse.

“We had two guiding lights while building Vertex AI: get data scientists and engineers out of the orchestration weeds, and create an industry-wide shift that would make everyone get serious about moving AI out of pilot purgatory and into full-scale production,” said Andrew Moore, vice president and general manager of Cloud AI and Industry Solutions at Google Cloud. “We are very proud of what we came up with in this platform, as it enables serious deployments for a new generation of AI that will empower data scientists and engineers to do fulfilling and creative work.”

At long last, the Monday.com crew dropped an F-1 filing to go public in the United States. TechCrunch has long known that the company, which sells corporate productivity and communications software, has scaled north of $100 million in annual recurring revenue (ARR).

The countdown to its IPO filing — an F-1, because the company is based in Israel, rather than the S-1s filed by domestic companies — has been ticking for several quarters, so seeing Monday.com drop the document on this Monday morning was just good fun.

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The Exchange has been riffling through the document since it came out, and we’ve picked up on a few things to explore. We’ll start by looking at the company’s revenue growth on a historical basis to see if it has accelerated in recent quarters thanks to the pandemic. Then, we’ll turn to profitability, cash burn, share-based compensation expenses and product vision.

We’ll wrap at the end with a summary of what we’ve learned and also make sure to check out the company’s marketing spend, because I’m sure you’ve seen its digital ads.

It’s a lot to chew through, so no more dilly-dallying. Into the numbers!

As always, we’re starting with revenue growth because it’s still the single most important thing about any venture-backed company.

Revenue adds are accelerating

This is great news for the startup, its employees and its investors. From 2019 to 2020, Monday.com grew its revenues from $78.1 million to $161.1 million, or 106%.

From Q1 2020 to Q1 2021, the company’s revenues grew from $31.9 million to $59 million. That’s about 85% growth. So, by what measure do we mean that the company’s revenue growth is accelerating? Its sequential-quarter revenue growth is picking up. Observe the following:

From Q2 2019 to Q3 2019, the company added around $4 million in revenue. From Q2 2020 to Q3 2020, that number was $6.1 million. More recently, the company’s revenue added $7.6 million from Q3 2020 to Q4 2020, which accelerated to $8.8 million from the final quarter of 2020 to the first quarter of 2021. Of course, from an ever-larger base, the company’s growth rate may decline. But the super clean and obvious expanding sequential revenue gains at the company are solid.

The fact that it added so much top line in recent quarters also helps explain why Monday.com is going public now. Sure, the markets are still near record highs and the pandemic is fading, but just look at that consistent growth! It’s investor catnip.

For Bill Staples, the freshly appointed CEO at New Relic, who takes over on July 1, yesterday was a good day. After more than 20 years in the industry, he was given his own company to run. It’s quite an accomplishment, but now the hard work begins.

Lew Cirne, New Relic’s founder and CEO, who is stepping into the executive chairman role, spent the last several years rebuilding the company’s platform and changing its revenue model, aiming for what he hopes is long-term success.

“All the work we did in re-platforming our data tier and our user interface and the migration to consumption business model, that’s not so we can be a $1 billion New Relic — it’s so we can be a multibillion-dollar New Relic. And we are willing to forgo some short-term opportunity and take some short-term pain in order to set us up for long-term success,” Cirne told TechCrunch after yesterday’s announcement.

On the positive side of the equation, New Relic is one of the market leaders in the application performance monitoring space. Gartner has the company in third place behind Dynatrace and Cisco AppDynamics, and ahead of DataDog. While the Magic Quadrant might not be gospel, it does give you a sense of the relative market positions of each company in a given space.

New Relic competes in the application performance monitoring business, or APM for short. APM enables companies to keep tabs on the health of their applications. That allows them to cut off problems before they happen, or at least figure out why something is broken more quickly. In a world where users can grow frustrated quickly, APM is an important part of the customer experience infrastructure. If your application isn’t working well, customers won’t be happy with the experience and quickly find a rival service to use.

In addition to yesterday’s CEO announcement, New Relic reported earnings. TechCrunch decided to dig into the company’s financials to see just what challenges Staples may face as he moves into the corner office. The resulting picture is one that shows a company doing hard work for a more future-aligned product map and business model, albeit one that may not generate the sort of near-term growth that gives Staples ample breathing room with public investors.

Near-term growth, long-term hopes

Making long-term bets on a company’s product and business model future can be difficult for Wall Street to swallow in the near term. But such work can garner an incredibly lucrative result; Adobe is a good example of a company that went from license sales to subscription incomes. There are others in the midst of similar transitions, and they often take growth penalties as older revenues are recycled in favor of a new top line.

So when we observe New Relic’s recent result and guidance for the rest of the year, we’re more looking for future signs of life than quick gains.

Starting with the basics, New Relic had a better-than-anticipated quarter. An analysis showed the company’s profit and adjusted profit per share both beat expectations. And the company announced $173 million in total revenue, around $6 million more than the market expected.

So, did its shares rise? Yes, but just 5%, leaving them far under their 52-week high. Why such a modest bump after so strong a report? The company’s guidance, we reckon. Per New Relic, it expects its current quarter to bring 6% to 7% growth compared to the year-ago period. And it anticipates roughly 6% growth for its current fiscal year (its fiscal 2022, which will conclude at the end of calendar Q1 2022).

More money for the now very buzzy business of reshaping how people work: Worksome is announcing it recently closed a $13 million Series A funding round for its “freelance talent platform” — after racking up 10x growth in revenue since January 2020, just before the COVID-19 pandemic sparked a remote working boom.

The 2017 founded startup, which has a couple of ex-Googlers in its leadership team, has built a platform to connect freelancers looking for professional roles with employers needing tools to find and manage freelancer talent.

It says it’s seeing traction with large enterprise customers that have traditionally used Managed Service Providers (MSPs) to manage and pay external workforces — and views employment agency giants like Randstad, Adecco and Manpower as ripe targets for disruption.

“Most multinational enterprises manage flexible workers using legacy MSPs,” says CEO and co-founder Morten Petersen (one of the Xooglers). “These largely analogue businesses manage complex compliance and processes around hiring and managing freelance workforces with handheld processes and outdated technology that is not built for managing fluid workforces. Worksome tackles this industry head on with a better, faster and simpler solution to manage large freelancer and contractor workforces.”

Worksome focuses on helping medium/large companies — who are working with at least 20+ freelancers at a time — fill vacancies within teams rather than helping companies outsource projects, per Petersen, who suggests the latter is the focus for the majority of freelancer platforms.

“Worksome helps [companies] onboard people who will provide necessary skills and will be integral to longer-term business operations. It makes matches between companies and skilled freelancers, which the businesses go on to trust, form relationships with and come back to time and time again,” he goes on.

“When companies hire dozens or hundreds of freelancers at one time, processes can get very complicated,” he adds, arguing that on compliance and payments Worksome “takes on a much greater responsibility than other freelancing platforms to make big hires easier”.

The startup also says it’s concerned with looking out for (and looking after) its freelancer talent pool — saying it wants to create “a world of meaningful work” on its platform, and ensure freelancers are paid fairly and competitively. (And also that they are paid faster than they otherwise might be, given it takes care of their payroll so they don’t have to chase payments from employers.)

The business started life in Copenhagen — and its Series A has a distinctly Nordic flavor, with investment coming from the Danish business angel and investor on the local version of the Dragons’ Den TV program Løvens Hule; the former Minister for Higher Education and Science, Tommy Ahlers; and family home manufacturer Lind & Risør.

It had raised just under $6M prior to thus round, per Crunchbase, and also counts some (unnamed) Google executives among its earlier investors.

Freelancer platforms (and marketplaces) aren’t new, of course. There are also an increasing number of players in this space — buoyed by a new flush of VC dollars chasing the ‘future of work’, whatever hybrid home-office flexible shape that might take. So Worksome is by no means alone in offering tech tools to streamline the interface between freelancers and businesses.

A few others that spring to mind include Lystable (now Kalo), Malt, Fiverr — or, for techie job matching specifically, the likes of HackerRank — plus, on the blue collar work side, Jobandtalent. There’s also a growing number of startups focusing on helping freelancer teams specifically (e.g. Collective), so there’s a trend towards increasing specialism.

Worksome says it differentiates vs other players (legacy and startups) by combining services like tax compliance, background and ID checks and handling payroll and other admin with an AI powered platform that matches talent to projects.

Although it’s not the only startup offering to do the back-office admin/payroll piece, either, nor the only one using AI to match skilled professionals to projects. But it claims it’s going further than rival ‘freelancer-as-a-service’ platforms — saying it wants to “address the entire value chain” (aka: “everything from the hiring of freelance talent to onboarding and payment”).

Worksome has 550 active clients (i.e. employers in the market for freelancer talent) at this stage; and has accepted 30,000 freelancers into its marketplace so far.

Its current talent pool can take on work across 12 categories, and collectively offers more than 39,000 unique skills, per Petersen.

The biggest categories of freelancer talent on the platform are in Software and IT; Design and Creative Work; Finance and Management Consulting; plus “a long tail of niche skills” within engineering and pharmaceuticals.

While its largest customers are found in the creative industries, tech and IT, pharma and consumer goods. And its biggest markets are the U.K. and U.S.

“We are currently trailing at +20,000 yearly placements,” says Petersen, adding: “The average yearly spend per client is $300,000.”

Worksome says the Series A funding will go on stoking growth by investing in marketing. It also plans to spend on product dev and on building out its team globally (it also has offices in London and New York).

Over the past 12 months the startup doubled the size of its team to 50 — and wants to do so again within 12 months so it can ramp up its enterprise client base in the U.S., U.K. and euro-zone.

“Yes, there are a lot of freelancer platforms out there but a lot of these don’t appreciate that hiring is only the tip of the iceberg when it comes to reducing the friction in working with freelancers,” argues Petersen. “Of the time that goes into hiring, managing and paying freelancers, 75% is currently spent on admin such as timesheet approvals, invoicing and compliance checks, leaving only a tiny fraction of time to actually finding talent.”

Worksome woos employers with a “one-click-hire” offer — touting its ability to find and hire freelancers “within seconds”.

If hiring a stranger in seconds sounds ill-advised, Worksome greases this external employment transaction by taking care of vetting the freelancers itself (including carrying out background checks; and using proprietary technology to asses freelancers’ skills and suitability for its marketplace).

“We have a two-step vetting process to ensure that we only allow the best freelance talent onto the Worksome platform,” Petersen tells TechCrunch. “For step one, an inhouse-built robot assesses our freelancer applicants. It analyses their skillset, social media profiles, profile completeness and hourly or daily rate, as well as their CV and work history, to decide whether each person is a good fit for Worksome.

“For step two, our team of talent specialists manually review and decline or approve the freelancers that pass through step one with a score of 85% or more. We have just approved our 30,000th freelancer and will be able to both scale and improve our vetting procedure as we grow.”

A majority of freelancer applicants fail Worksome’s proprietary vetting processes. This is clear because it says it has received 80,000 applicants so far — but only approved 30,000.

That raises interesting questions about how it’s making decisions on who is (and isn’t) an ‘appropriate fit’ for its talent marketplace.

It says its candidate assessing “robot” looks at “whether freelancers can demonstrate the skillset, matching work history, industry experience and profile depth” deemed necessary to meet its quality criteria — giving the example that it would not accept a freelancer who says they can lead complex IT infrastructure projects if they do not have evidence of relevant work, education and skills.

On the AI freelancer-to-project matching side, Worksome says its technology aims to match freelancers “who have the highest likelihood of completing a job with high satisfaction, based on their work-history, and performance and skills used on previous jobs”.

“This creates a feedback loop that… ensure that both clients and freelancers are matched with great people and great work,” is its circular suggestion when we ask about this.

But it also emphasizes that its AI is not making hiring decisions on its own — and is only ever supporting humans in making a choice. (An interesting caveat since existing EU data protection rules, under Article 22 of the GDPR, provide for a right for individuals to object to automated decision making if significant decisions are being taken without meaningful human interaction.) 

Using automation technologies (like AI) to make assessments that determine whether a person gains access to employment opportunities or doesn’t can certainly risk scaled discrimination. So the devil really is in the detail of how these algorithmic assessments are done.

That’s why such uses of technology are set to face close regulatory scrutiny in the European Union — under incoming rules on ‘high risk’ users of artificial intelligence — including the use of AI to match candidates to jobs.

The EU’s current legislative proposals in this area specifically categorize “employment, workers management and access to self-employment” as a high risk use of AI, meaning applications like Worksome are likely to face some of the highest levels of regulatory supervision in the future.

Nonetheless, Worksome is bullish when we ask about the risks associated with using AI as an intermediary for employment opportunities.

“We utilise fairly advanced matching algorithms to very effectively shortlist candidates for a role based solely on objective criteria, rinsed from human bias,” claims Petersen. “Our algorithms don’t take into account gender, ethnicity, name of educational institutions or other aspects that are usually connected to human bias.”

“AI has immense potential in solving major industry challenges such as recruitment bias, low worker mobility and low access to digital skills among small to medium sized businesses. We are firm believers that technology should be utilized to remove human bias’ from any hiring process,” he goes on, adding: “Our tech was built to this very purpose from the beginning, and the new proposed legislation has the potential to serve as a validator for the hard work we’ve put into this.

“The obvious potential downside would be if new legislation would limit innovation by making it harder for startups to experiment with new technologies. As always, legislation like this will impact the Davids more than the Goliaths, even though the intentions may have been the opposite.”

Zooming back out to consider the pandemic-fuelled remote working boom, Worksome confirms that most of the projects for which it supplied freelancers last year were conducted remotely.

“We are currently seeing a slow shift back towards a combination of remote and onsite work and expect this combination to stick amongst most of our clients,” Petersen goes on. “Whenever we are in uncertain economic times, we see a rise in the number of freelancers that companies are using. However, this trend is dwarfed by a much larger overall trend towards flexible work, which drives the real shift in the market. This shift has been accelerated by COVID-19 but has been underway for many years.

“While remote work has unlocked an enormous potential for accessing talent everywhere, 70% of the executives expect to use more temporary workers and contractors onsite than they did before COVID-19, according to a recent McKinsey study. This shows that businesses really value the flexibility in using an on-demand workforce of highly skilled specialists that can interact directly with their own teams.”

Asked whether it’s expecting growth in freelancing to sustain even after we (hopefully) move beyond the pandemic — including if there’s a return to physical offices — Petersen suggests the underlying trend is for businesses to need increased flexibility, regardless of the exact blend of full-time and freelancer staff. So platforms like Worksome are confidently poised to keep growing.

“When you ask business leaders, 90% believe that shifting their talent model to a blend of full-time and freelancers can give a future competitive advantage (Source: BCG),” he says. “We see two major trends driving this sentiment; access to talent, and building an agile and flexible organization. This has become all the more true during the pandemic — a high degree of flexibility is allowing organisations to better navigate both the initial phase of the pandemic as well the current pick up of business activity.

“With the amount of change that we’re currently seeing in the world, and with businesses are constantly re-inventing themselves, the access to highly skilled and flexible talent is absolutely essential — now, in the next 5 years, and beyond.”