An Enterprise AI Showdown – C3 Stock vs. Palantir Stock

A reader recently dropped by to say that our content would get us on Howard Stern before it landed us a Ted talk. It’s compliments like that which keep us going and let us know our snark is set to an appropriate level. Sometimes saying things how they are is seen as being iconoclastic, and we’re okay with that.

Saying things how they are is also authentic, something people like. You’ll inevitably show your flaws, and then they’ll like you even more (the pratfall effect). Unlike other financial pundits, we don’t assume the reader knows what EBITDA is, or even cares for that matter. Most of the financial world is extremely boring and pretentious. We want to take what little is useful and leave the rest.

The Nanalyze Disruptive Tech Investing Methodology focuses on things like revenue growth, as-a-service business models, and favorable competitive situations. We avoid taking risks by looking for red flags. We buy quality tech stocks and let time do what it does best. So, it’s in that spirit that we’re going to open a can of worms. We’re going to try and compare two enterprise artificial intelligence (AI) stocks – C3 vs. Palantir – by answering questions like:

  • Do they do similar things? Are they close or distant competitors competing for the same total addressable market? The same segments?
  • Are they valued the same? Valuation is a tricky thing to measure
  • Are there any risks that are showstoppers, things like customer concentration risk?
  • What are each company’s future growth prospects?

C3 vs. Palantir

Our title is total clickbait because it’s hardly a showdown if C3 plays darts and Palantir plays cricket. While both these sports are similar because they’re enjoyed by people who are bored out their minds, they’re hardly competing with one another for fans. The same might hold true for C3 and Palantir, so let’s start by more closely defining what each company does in the simplest of terms.

What Palantir Does

Click for company website

Palantir is a central operating system for an organization’s data that helps them make sense of it – at scale. The example given is an Airbus which “has five million parts and is built by hundreds of teams that are spread across four countries and more than eight factories.” Palantir’s software can be up and running in hours, and they can deploy changes very quickly. Flexibility in enterprise software isn’t the norm, and Palantir isn’t a normal enterprise software company. That happens to be what C3 says too. On the fourth page of their S-1 filing document – “the key to success is C3’s ability to bring high-value enterprise AI applications into production use rapidly.”

What C3 Does

Click for company website

C3’s stated goal is none other than to “establish and maintain a global leadership position in Enterprise AI across all market segments including large enterprises, small and medium businesses, and government entities.” They claim to have the leading enterprise AI platform, and their CEO and Founder, Tom Siebel, is a legend in the tech world with a proven track record of growing companies and selling them. In a 2019 keynote address, he talks about the opportunity for “digital innovation,” and emphasizes the speed at which his team can deploy their platform. In the company’s own words, “it boils down to execution risk.”

Without digging into the technical details, we can say that both companies provide comprehensive technology platforms that ingest incredibly large amounts of data from huge ecosystems and make sense of it. In the olden days, this would be equated to implementing an enterprise resource planning (ERP) platform (like SAP) that allowed a company to take a holistic look at their organization. An ERP project might take years, even decades, to deploy. Even then, it often lacks flexibility, hardly being able to handle things like making sense of unstructured data, or easily ingesting proprietary vendor reports.

For any customer to build a system like this in-house, they would need to stitch together many third party solutions which would take a massive effort over a long period of time, and a sophisticated IT and data engineering team.

Matt Turck on Palantir

The bulky awkwardness of traditional full-stack enterprise software platforms is obvious when you find consultants using UiPath to make sense of a SAP implementation.

While both Palantir and C3 are developing full-stack enterprise AI offerings and coming off of IPOs in 2020, they differ dramatically in size, something that’s a proxy for maturity. Here’s a look at the relative size of some companies that could be classified as “enterprise AI.”

Palantir is 6X the size of C3 – Credit: Nanalyze

Let’s use the above market caps to produce a ratio that will help us measure relative valuation.

C3 vs. Palantir – Which is Fairly Valued?

Measuring the relative valuation of multiple companies can quickly become a can of worms that tells us nothing. Just look at how useless SPAC comparable slides have become. In order to compare how two companies are relatively valued, we can use a simple ratio such as “size divided by sales.” When calculating “sales,” we can take the last reported quarter and then multiply it by four as if to say “this is how much revenue the company would produce in the next year if nothing changes.” Below we calculate our simple valuation ratio using Tesla as an example:

  • Multiply 4Q-2020 revenues of $10.74 billion times four to get “annualized revenues” of $42.96 billion. Divide Tesla’s market cap of $702 billion by $42.96 billion and we get a ratio of roughly 16.

In the same manner, we can take the market cap values from our previous chart and use them to produce a basic valuation ratio for all our enterprise AI companies.

Company NameRevenue DataAnnualized Revenues
(billions USD)
Ratio
Palantir4Q-2020*41.28835
UiPath2021 Actual0.60743
Splunk1Q-2021*42.988
C31Q-2021*40.19636
Alteryx4Q-2020*40.649
Blue Prism4Q-2020*40.28
Snowflake1Q-2021*40.7688

Both C3 and Palantir have around the same ratio, which tells us both something and nothing. At least, we have a benchmark to use going forward and a “common language” to use when discussing enterprise AI companies in their teenage growth years. At a later stage, these companies will become profitable, and we’ll want to use different metrics to assess progress instead of placing such a heavy emphasis on revenue-growth-at-all-costs.

Our simple valuation ratio is practically useless for mature companies where you need to consider things like profitability or projected growth which becomes more predictable as a company matures. Just look at how varied our valuation ratio becomes when applied to some of the world’s biggest enterprise software companies.

Company NameRevenue DataRevenues (billions USD)Ratio
Microsoft4Q-2020*44344
Oracle1Q-2021*4406
Salesforce1Q-2021*423.29
Adobe1Q-2021*415.616
SAP4Q-2020*4305

Our rudimentary “market cap / annualized revenues” ratio doesn’t work well for large enterprise software companies, but it does provide some usefulness in comparing enterprise AI companies with blue ocean opportunities that can achieve seemingly limitless amounts of growth in the early years of expansion.

C3 vs. Palantir – Current Customers

Matt Turck is a Partner at venture capital firm FirstMark, where he focuses mostly on early-stage enterprise and B2B investing. He reviewed the S-1 filings for Palantir and C3 while being careful not to directly compare the two. It’s easy enough to see how they’re similar. Says Mr. Turck, “Palantir is an enterprise software company with few customers (125 in total) and very large contracts.” So is C3 with their 59 customers and an average contract size of $14 million (Palantir’s average revenue per customer is around $7.9 million.) This has resulted in something we don’t like about both C3 and Palantir – customer concentration risk.

Mr. Turck explains how this concentration shows product-market fit. These solutions would be impossible for any large company to build without investing years of time and billions of dollars. These large customers can afford to pay the steep fees these platforms command, especially when it comes out of the money they’re saving. It only makes sense that both C3 and Palantir focus on large companies of which there are plenty to go around.

The key difference between who these companies service is an overreliance by Palantir on the U.S. government. It’s their stated goal to become “the default operating system for data across the U.S. government.” When working with a government that happens to also reside in the same country that you do means they have all the leverage. We don’t believe that any single customer should represent more than 10% of a company’s revenues. In 2020, 56% of Palantir’s revenues came from customers in the government segment, and we believe that represents a risk that should be avoided.

Buy C3 Stock or Palantir Stock?

Battle-hardened leadership teams have a better chance at succeeding. Some might argue Tom Siebel already had his day in the sun, while others might disagree with how Palantir rubs people the wrong way at times as it flirts with the edges of politics. We find Mr. Siebel’s story to be extremely compelling, while also admiring Palantir for having the cojones to say what they think. As risk-averse investors, we’d like to know which of these leaders has a lesser chance of failing? In the end, we’re staying with C3, and hoping they have a lot of room to grow as they continue focusing on hiring only the best talent in the world. (It’s one of the most competitive places we know of to get a job with just 0.412% of applications resulting in a hire.)

The enterprise AI thesis is very simple. The powers of AI are being used to add value (increase revenues and decrease costs), something which has been developed into a recurring revenue business model. Because AI is continuously improving and will never stop, companies will continue to pay for these AI-powered services every year, and cancelation rates will be low. Growth may slow, but it should never decline. Eventually, these enterprise AI vendors will be acquired or merge with each other leading to some giant enterprise software success stories. As long as we have some skin in the game across a few of the leaders, we should enjoy superior returns from enterprise AI. There is room for many winners because the total addressable market is so huge.

Conclusion

Both C3 and Palantir have full-stack AI offerings that can be built quickly and flexibly. The triple-digit total addressable market they’re both selling to is so big that these companies could expand for a decade without ever crossing paths. After all, they’re both focused on small numbers of clients that produce large streams of revenues. There’s no need to compete when there’s plenty to go around, but that changes over time as market leaders start to emerge. Regardless of which stock you choose to invest in, be prepared for lots of continued volatility.

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4 thoughts on “An Enterprise AI Showdown – C3 Stock vs. Palantir Stock
  1. If we are talking about enterprise AI we cannot ignore Darktrace (DARK.L). It had IPO very recently.
    —-

    Darktrace is a world leading provider of AI for the enterprise, with the first at scale deployment of AI in cyber security, and a pioneer of autonomous response technology. Created by mathematicians, our platform uses machine learning and AI algorithms to neutralise cyber threats across diverse digital estates, including the cloud and networks, IoT and industrial control systems.

    Darktrace sees its total addressable market (TAM) at $40bn. Assuming that’s an accurate calculation, then the company has a small 0.5% market share. That would suggest ample room for continued revenue growth, particularly if the TAM grows as fast as the broader information security and risk management market. Gartner, a research and advisory firm, thinks the broader market will grow 8.2% per annum through 2024.

    1. Stan, you’re quite prolific when it comes to comments, so we shortened this one. 😉

      Firstly, Darktrace isn’t “enterprise AI.” At least not how we define it. They’re a cybersecurity company, and not the only one using AI.

      Secondly, there seems to be a discount that foreign traded firms command which merits a look. They don’t suffer from “the ARK effect” because ARK admittedly is domestically biased. So, we do plan to write about Darktrace, but we have a lot in the queue at the moment. We do think it merits a look so stay tuned man.

  2. C3.ai is trading near its 52 week low. Current price: $50.53. 52 week range: $47.22 – $183.90.
    So the obvious question arises: is it a bargain now ?
    Market cap: $5.2B, latest annualized revenue: $212M. So the ratio is: 24.5.
    They burn $24M per quarter. Cash: $1B – that looks very good comparing to cash burn.
    1 year revenue growth forecast is 33% – that is quite moderate growth for an expensive stock.
    One thing I find worrying is: analysts cannot agree on that stock: I see 1 strong buy but also 2 strong sell ratings.
    So taking all of these into account: I am not convinced it is a bargain now.

    1. Forget what analysts agree on. That’s absolutely useless. Make your own decisions based on your own convictions. We’ve been buyers based on our own convictions. We may not be buying at the bottom, but we’re slowly accumulating based on our own convictions and situation. Everyone will have a different situation.

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