A member of our Emerging MAD Index of companies on their path to an IPO, Confluent is a very interesting company in a strategic part of the data space, providing infrastructure for real-time data streaming – what it nicely calls “data in motion”, in contrast to the world of batch processing or “data at rest”.
I had the pleasure of hosting the company’s co-founder and then CTO, Neha Narkhede, at Data Driven NYC back in 2016, and her great talk remains entirely relevant to understand the premise behind the company and its core technical foundation.
For anyone following the software industry, there’s been a little bit of snark about C3.ai (“C3”) over the years. Here’s a company that was founded by Silicon Valley royalty (Tom Siebel, who sold Siebel Systems to Oracle in 2006 for just shy of $6B), with seemingly limitless access to capital, that somehow seemed to be pivoting every few years to something new – from energy at first, to the Internet of Things, to Artificial Intelligence.
C3 also largely eschewed the startup echochamber – funded personally by its founder at first, it didn’t raise money from the usual VC suspects, target well-know startups as its first customers, or open source any AI frameworks, working instead with a small group of Fortune 1000 and government customers. As a result, it didn’t build the kind of buzz that often precedes the most notable startups on their way to becoming public.
Lo and behold, what emerges in this IPO is a solid company by enterprise software IPO standards, with $157m in revenue, growing 71% yoy, a 75% gross margin and a $69m loss.
It will be interesting to see how the market reacts to this IPO.
On the one hand, C3 is not growing anywhere as explosively as a Snowflake, and in fact seems to have just had a bad quarter of decelerating growth. There are also other concerns, including account concentration and a substantial loss (not as pronounced as a Snowflake or Palantir, but still on the higher range of the software market).
On the other hand, the tailwinds around the deployment of ML/AI in the enterprise are very strong, and C3 is clearly positioning itself as one of the very first enterprise AI companies to go public: its ticker symbol on the NYSE will be “AI”, and the term “machine learning” is mentioned 56 times in the S-1.
This IPO will be an interesting test for the continued appetite of financial markets for all things AI.
Here’s a quick analysis of the S-1 and main characteristics of the business, put together by my FirstMark colleague John Wu and I.
The Palantir S-1 is a long and meaty read, and a pretty fascinating one considering the company was highly secretive, and often controversial, for so many years. It is also written in a very opinionated style: the newly Colorado-based company takes aim at Silicon Valley and is not exactly charitable to its competitors.
Particularly compared to a Snowflake that has had a meteoric rise since inception in 2012 (see our Snowflake teardown here), the Palantir S-1 also presents the picture of a company that, while unique, has had a long road since it was founded in 2003.
It seems that the company went through an important transition in the last couple of years on the product and go to market front – evolving away from a services company into more of a software one – perhaps in anticipation of an IPO.
Ironically, in some ways, this evolution has made Palantir look more like the Silicon Valley companies it feels so different from.
Here are some quick thoughts and notes (from Avery Klemmer and myself)
The Snowflake IPO is shaping up to be particularly exciting. Their S-1 shows very impressive metrics across the board, including explosive revenue growth at scale (growing 174% annually to $264.7 million for the fiscal year ended January 31, 2020), and “land and expand” motion (169% net revenue retention in 2020), making Snowflake one of the fastest growing enterprise companies ever.
In addition to the intrinsic merits of the company, this is yet another example showing how gigantic the market is for data technologies (storage, analytics, machine learning, etc.). Snowflake estimates its addressable market at $81B.
We’ve had the pleasure of hosting Snowflake’s former CEO, Bob Muglia, a couple of times at our Data Driven NYC event of the years (see videos below), and it’s been really fun to watch the company grow.
[July 14, 2020 IPO update – stock popped + 195% first day of trading, see end of post for details on IPO]
The upcoming nCino IPO is an interesting story, and a good reminder that strong cloud/SaaS companies can be built outside of the usual Silicon Valley or NYC venture path (even with VCs on board)
(As a side note: we often do those S-1 summaries internally to keep tabs on the software IPO market, so my colleague Avery Klemmer and I figured we’d “open source” this one in case it might be interesting to others – thoughts and comments welcome. Our firm FirstMark is not an investor in nCino)
HIGH LEVEL THOUGHTS & LESSONS:
nCino is a refreshing example of a successful software company that’s built a little bit outside of what’s currently in favor in venture capital circles:
Vertical software: Many VCs these days tend to prefer broad horizontal opportunities, with a concern that vertical software ultimately has a limited TAM, even a large one – but nCino is 100% focused on the banking market
Service heavy, no bottoms up GTM: nCino sells its products through AEs , with long sales cycles, and significant implementation services are involved
Platform dependency? Being built on top of someone else’s platform is often a concern for investors. nCino is built on top of Salesforce (like Veeva). They’ve seemingly safeproofed this relationship by reselling Salesforce products in their deals, and raising money from Salesforce, wnich is a large investor.
Not a Silicon Valley or NYC story: Launched in 2012 by executives of North Carolina-based Live Oak Bank as a spin-off venture. Still based in Wilmington, North Carolina
It’s a spinoff from a bank: the company was originally founded as a majority-owned subsidiary of Live Oak Bancshares, a bank holding company. It then raised $9m in seed funding in 2013 from a variety of individuals including John Mack of Morgan Stanley and Chip Mahan, the Chairman of Live Oak Bank. So nCino didn’t have the structure that most VCs like to see, where the founding team has high ownership and the first money in comes from institutional investors. This history as a spin-off is probably the reason why the CEO of the company owned only 1.6% at IPO time, although we don’t know this for sure).
The Datadog IPO just happened, and it’s proven to be a resounding success, not surprisingly given the company’s superb metrics – big revenues ($333M ARR), happy customers that keep buying more (146% net revenue retention) and, unlike many others, a history of profitability. To make the story even more epic, it transpired that the company had turned down a last minute big acquisition offer from Cisco shortly before the IPO, which valued the company higher than its proposed IPO range.
While I’m a small personal shareholder in the company and friendly with its founders, this is not going to be a VC victory lap kind of a post, for the simple reason that I did not invest in the company as a VC (as the early rounds of financing took place before my current tenure, in my defense!).
Regardless, I wanted to write a few quick thoughts, as I believe this particular IPO should be loudly celebrated.
The superb Lending Club success story is what the startup world is all about: a software-based reinvention of massive and inefficient industry; a product that puts consumers first and delivers undeniable benefits ; and an entrepreneurial mega-hit that brings incredible riches and returns to its founder and investors.
In some ways, Lending Club is a classic Silicon Valley story; in some other ways, it is pretty atypical. As a friend of Renaud Laplanche’s for over 20 years, I have had a chance to witness from up close some parts of his journey with Lending Club. It is full of interesting lessons for entrepreneurs and the tech industry in general: