Transcription
Paler has a huge problem. Thanks to artificial intelligence, new innovations are coming out faster than ever before, which means that Paler cutting AI today could become a commodity by tomorrow. So in this episode, I'll show you why Paler could be doomed as early as 2024, even if they technically still have the best AI platforms. Your time is valuable, so let's get right into it.
Let me start by saying that this isn't a video about Paler somehow being bad, and I'm not rooting for them to fail. I actually got to use Foundry for myself, and I was blown away by everything I saw it do. During that time, I had weekly meetings with Paler staff members, where we planned out a project, connected my Foundry instance to a few interesting data sources, built a small ontology, and then put together a few pipelines and dashboards to analyze changes in my data over time. Beyond that, Paler employees were smart, patient, and treated me like a real customer, even though my project was obviously tiny in comparison to everything else they do.
As I learned more about Foundry, it became obvious that I was just scratching the surface of its full capabilities. So, I eventually stopped worrying about my project altogether and started testing every tool, reading every document, and asking every question I could think of before giving up my Foundry access about a year ago.
So, the first thing I want to say is a big thank you to everyone at Paler who I had the privilege of working with last year, and a huge thank you to Cod Strap for connecting us in the first place. What an absolute legend!
The next thing I'm sure you want to know is why I haven't really covered Paler since I got access to Foundry. After all, that was the whole point of me using it. Long story short, Foundry costs money, which means that Paler was technically compensating me by giving me access. I also had to sign nondisclosure agreements because my instance of Foundry and my meetings both included features that were still being worked on. So that really limited what I could record, not to mention that showing anything in a YouTube video would mean me technically making money with Foundry, which brought up even more issues.
In the end, I got some pretty clear guidance on what I couldn't say, show, or do with my Foundry access. According to the FTC and SEC regulations, that guidance is what kept me quiet about Paler this whole time. Now that it's been a full year since I gave up my Foundry access and got offboarded from Paler, I can talk about everything that's changed. And boy, has the world changed! New industries, new competitors, and of course, a new era of AI. Paler has changed a bit as well—new partnerships, new platforms, and new quarterly reports.
So let's talk about all of these changes and what they could mean for Paler in 2024. First things first, it's never been a more important time to understand the science behind this stock. You tell me: who is your daddy and what does he do?
If you've seen my previous Paler videos, you have a huge leg up over other investors because you understand what this company does. And if you understand that, you know who actually competes with them. And they do have some serious competition, which I'll talk about in a little bit. If you don't know what Paler does, here's the 60-second speedrun:
Paler's Gotham and Foundry platforms enable data science across an entire enterprise by giving everyone—from executives and engineers to sales teams and human resources—a consistent, real-time view of their data. They do that by helping companies create digital twins, which are also called ontologies. At a high level, ontologies are networks of things and their relationships. The bigger the enterprise, the harder it usually is to get this step right.
For example, the US Army is a huge interconnected network of personnel, assets, locations, and objectives. Amazon is a network of warehouses, vendors, products, and customers. Facebook is a network of people, organizations, and places that are connected by their relationships.
Paler platforms help large enterprises build, maintain, and use these ontologies to track and analyze their resources and optimize their operations as things change, often in real-time. One big thing that separates Paler platforms from their competition is their ability to maintain extremely high levels of accuracy over many different kinds of data processing while complying with many different levels of access permissions and classifications.
While that may not sound particularly exciting, juggling accuracy, speed, and security is one of the toughest challenges for AI-based tools today, and it's especially important for the high-risk environments that Paler customers find themselves operating in—whether they're a branch of the US military, a big hospital complex, an international bank, or an airline. Both Gotham and Foundry can also connect directly to an asset and let users send commands directly from Paler software, like rotating a wind turbine, rerouting a vehicle, or even tasking a military unit.
That's actually an insane level of access and control to give to any third-party software, which shows just how much some of the biggest governments, militaries, and companies on the planet trust Paler platforms with their most sensitive data.
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All right, so the biggest enterprises on the planet trust Paler platforms with their most sensitive data. Last year, Forrester Research ranked Paler as the leading artificial intelligence and machine learning platform, beating out tech giants like Microsoft and Google, as well as more direct competitors like Databricks and C3 AI. And that's not even including AIP, Paler's artificial intelligence platform, which has become their most demanded product.
In a nutshell, companies can choose a large language model, like OpenAI's GPT-4 or Anthropic's Claude 2, and AIP will supercharge it by letting it access different Paler functions and algorithms, training it on the right parts of an ontology, automatically enforcing data and user permissions with the right guardrails, augmenting prompts to limit the model's hallucinations, and even teaching it to take pre-approved actions based on who's using it. AIP is seriously impressive, especially in a world where Google is still going viral for showing off how their AI models can recognize a duck.
I was just talking about a blue duck, and now you're holding one. It looks like blue ducks are more common than I thought. Good job, Gemini! What's that? The conversation was faked, and it didn't happen in real-time? Huh, no wonder Alex Karp keeps making fun of Silicon Valley all the time.
If you're sitting on your perch in Silicon Valley, and you're only creating value for yourself—monetizing your fellow Americans and others in the form of monetizing their data and providing no value to them except for disrupting the businesses that people work at—you're going to find that your level of trust goes really down, really far, quickly. I don’t think this is something you can kind of IQ your way out of, which is essentially one of the problems in Silicon Valley. They just think that they’re so smart that they can smart their way out of this, but you know, it's just so obvious.
Look, no one is debating that Paler makes some of the best AI-powered software platforms in the world. But being the best is not how companies dominate a market, which is a big problem for Paler because that seems to be their entire market strategy. During that earnings call, Alex Karp said, "We have no pricing strategy. We're going to create a lot of value, we're going to get hundreds of customers, and we will price it as we go."
Have you made any progress on the pricing strategy since that point? No. Why so relaxed about it? Because if you—it’s like one of these things, like when you go to a bar, everyone wants to meet you. Do you have a pricing strategy when you go to the bar? No. You're like, "Oh, I'm cool. I know we have the best product on the market. I know customers will pay us fairly. I know that it's much more valuable than anyone will understand until they install it and we will work it out. We are going to create a lot of value, and we're going to get some portion of that value. Customers are smart; they'll pay you some portion of the value."
Why should I just—as an acatic thing—if you have a software product, you always want to get paid after you deliver value. If you’ve got a PowerPoint, something that doesn’t work, something that's not valuable, you want to get paid before you create value. We know it’s valuable; we know it’s much more valuable than people understand, we know we're going to continue to augment that value, and we're going to get paid along the way.
The thing is, superior products almost always end up losing to inferior products with better branding and distribution, better pricing, lower switching costs, or just plain easier to use. That's because it's not the technology inside the product that matters—it's the product-market fit. If you don't believe me, maybe you'll believe Steve Jobs:
"You've got to start with the customer experience and work backwards to the technology. You can't start with the technology and try to figure out where you're going to try to sell it. And I've made this mistake probably more than anybody else in this room, and I've got the scar tissue to prove it. And I know that it's the case. And as we have tried to come up with a strategy and a vision for Apple, it started with what incredible benefits can we give to the customer? Where can we take the customer? Not starting with, let's sit down with the engineers and figure out what awesome technology we have and then how are we going to market that."
I know we have the best product on the market. I know customers will pay us fairly. I know that it's much more valuable than anyone will understand until they install it. If Alex Karp wasn't so wrapped up in the technology and instead focused on the needs of the companies in the commercial markets that he wants to capture, which have changed drastically over the last year, he would see that Paler does have some real competition from products like Microsoft Fabric, which can aggregate data, extract, organize, and transform it, storing it in a unified data lake right on Azure.
Administrators can manage permissions for that data, and users can build dashboards to analyze it in real-time. Companies can even build custom solutions on top of Fabric or embed different parts of Fabric in their existing applications. Fabric isn't just a concept; Microsoft announced Fabric's general availability just last month. Or how about Amazon Q, which is Amazon Web Services' new generative AI assistant? Companies can connect Q to all of their organizational data, including third-party integrations like Salesforce, Microsoft, and Google.
Q uses that data to answer questions, generate insights, and take action on behalf of the user—whether that means building and testing new applications, answering specific questions about a customer or service, or helping decision-makers visualize and analyze important data. Of course, Q understands existing user roles and permissions and limits its functionality accordingly.
Nobody is saying that Microsoft Fabric or Amazon Q are better than Paler’s Foundry. The reason that investors should worry about them anyway is because they help Paler target customers do more without Foundry in the first place, especially if they're already using other products and services from AWS or Azure.
Oh, and by the way, over 50% of all commercial businesses that would consider Paler’s Foundry already use at least one service from AWS or Azure today. Here's one more quick clip that I think really highlights everything wrong with Paler's current market strategy:
"You talked about the competitive landscape. I actually wanted to ask you about C3.ai as an example because you come up in bidding processes with them."
"Actually, we look—this is a massive market. We actually don't come up with bidding processes with anyone. And I'll tell you what I think about everyone."
So you don't have any competition?
"Let me just tell you about this competition thing that Wall Street analysts love: it's complete BS. This is an infinite market. Basically, try what we're doing and try what everyone else is doing and buy the thing that creates the most value in an infinite market."
Bloomberg Intelligence put out this research report this morning that says generative AI as a market will be $1.3 trillion in 2032 that requires compound annual growth of about 40% a year from this point over a decade.
Do you see that as realistic?
"What I see? I don't know based on the markets you operate in. Look, these experts just make stuff up. But you know what we know is this is a large, basically impossible to measure market. And what we also know is everyone in the US is going to find ways to become more efficient and better using software, and a lot of that software is going to be AI-driven. We also know that the market over time, not in a quarter, will end up picking the best products. That's what we know."
All right, I won't rehash the whole competition thing, but let me ask you a few different questions. Whether you believe Bloomberg's estimates that the AI market will grow by over 40% per year for the next decade, or Alex Karp when he says it's an infinite market already, then why did Paler's most recent earnings call only show 177% revenue growth year-over-year?
And how come their net dollar retention rate is just 107%? Net dollar retention measures how much money recurring customers spend with a company year-over-year. So, Paler's recurring customers spent just 7% more with them this year than last year. If it's lower because of headwinds in Europe like their earnings report suggests, then why not show the US numbers or the government versus commercial numbers, like they already do everywhere else?
And if they really have no competition in the commercial sector, then how come more than half of the revenue still comes from government customers? Hopefully, you're starting to see the disconnect between the rhetoric and reality here.
I know this video is a little long, but I want to be thorough since these are the things stopping Paler from growing faster. I haven't really been able to talk about them since I got access to Foundry. So if you feel I've earned it, consider hitting the like button and subscribing to the channel. That really helps me out and it lets me know to put out more commentary like this.
Thanks, and with that out of the way, there's really only one question left to answer: Is Paler actually doomed in 2024? No, of course not. But not being doomed isn't the same thing as reaching your full potential. And if there's one thing that every Paler shareholder agrees on, it's that this company has the potential to be massive.
Since I don't like complaining without offering solutions, here's something I think Paler could do to realize more of that potential: I would build a huge fictional data set that they can use for product demos, user training, and marketing. I'm talking recreating the entire Empire from Star Wars—complete with chains of command, lists of ship, troop and droid movements, and communications across different cities and planets, dynamic logistics, supply routes, mission objectives, and priority targets for those pesky Jedi and good-for-nothing Rebels.
Then, Paler can show off examples of how to set up new data sources, build out the Empire's entire ontology, and then interact with it through AIP and other analysis tools. Then I would use this giant data set to build an entire marketing campaign that shows off all of Paler's best tools and algorithms in detail and show how they all fit together using examples that most people in their target audience can actually understand—not just developers and computer scientists.
After that, I would start taking the most popular tools and algorithms from each platform and turning them into standalone services that can be sold separately and build a pricing strategy around them to capture more small and medium-sized businesses.
It doesn’t have to be every single feature, but I can already think of a few that make sense from my time with Foundry. This same data set can also be used for user training and certification, and even directly comparing Foundry to other products. Then everyone would clearly see why Alex Karp says Paler doesn't have any competition, because everyone would understand the science behind this stock. Until that happens, Paler is doomed to never reach its true potential.
Thanks for watching, and until next time, this is Ticker Symbol U. My name is Alex, reminding you that the best investment you can make is in you.