The $2 Million Edge: Get The Best AI In The World

Welcome, everybody. Welcome to today's latest training. We are going to be focusing on our proprietary FinSights AI, the best, the only AI for investing that you can trust. It's previously been available only to our professional and institutional clients. And we're bringing it out to the rest of the world at an individual investor price. And we're really excited about that today. I'm gonna jump right into this presentation. And I'm really excited to share it with you all today. So the $2 million edge, get the best AI in the world at our best price ever. This is a $2 million standalone product. Forget the millions that have gone into creating new constructs in our proprietary dataset and the training data. And all that proprietary, proven accurate research that I've talked about for years. On top of this, Google invested $2 million. They chose us to build this agent, and we're bringing it out to you for the first time ever for individual investors. Disclosures and disclaimers. We are not an investment advisory firm. We are not giving investment advice. We are giving you better information for making more informed decisions. I'm David Trainer. Nice to meet you. I'm a veteran of the tech bubble. I was there at Credit Suisse First Boston. Back then they called it CS First Boston, and it was the number one tech IPO investment banking firm. So I saw how the sausage was made. I met the people that wrote the emails. I can't believe anybody's stupid enough to invest in this piece of blank right after publishing reports to the world saying it was the greatest IPO ever. I met those people. I saw that happen, and I was inspired to create new constructs. I'm also the author of Modern Tools for Valuation, and I've been doing machine learning and AI for 25+ years. I wanna hear from you in the chat. Put your tickers in the chat. Now, the $2 million edge. Why this matters now? Because AI is everywhere, but trust is scarce. And this is an emerging topic, folks. We've been early on this for a long time, but you're reading this everywhere now. Alex Karp at Palantir is talking about it like crazy. He can't get enough, right? Because these big enterprises are paying the frontier models millions of dollars in tokens while giving away their IP. It's a terrible trade. Palantir does the opposite. And in many ways, they're like us. The first thing they do is they go to the client and they create an ontology for that data. And they build their own private AI, an AI that's private to that client so that their IP is not getting shared with the world. The noise is worse than ever in the stock market as well. Headlines around whether it's war, whether it's AI, which stocks should go up, which should go down, how generative AI is going to take over the world. They're trying to distract you from what matters most, which is the truth about most AI, which is that it's based on bad data. But there is a better way for you. Let me be blunt: most investors do not need more data; they need better information. There's a big difference. The internet is full of data; there's very little information there. But now let me be specific here. Most people are drowning in bad information and ideas, bad data. It's headlines, it's social media, it's analyst notes. Podcasts, chatbots. It's a cesspool out there. And if all those ideas are built on the same bad data, then what you really have is repetition, not insight. And that's what the chatbots are. You've also got the AI-created content all based on this internet. And that's a big thing that, you know, Alex Karp and a lot of experts, the CEO of IBM, they're saying the same thing. If you're building this AI on internet data. Larry Ellison saying the same thing. If you're building all these frontier models on the same junk internet data, you're not adding any value. It's not like these AI models are like alchemists for data. They can take the bad data and make it good data. There is no such thing. What investors need instead is truly reliable data, better filters, better rankings, better warnings, Better evidence, better diligence. All this is possible when you have an AI that's built on real data, verifiable, auditable data. So the real job of AI-driven research should be to help you avoid weak businesses, avoid bad valuations, find strong economics, find better setups. That's what AI should be doing for you. Right now, it's just repeating to you what you already know. Or what's popular. And you need answers from a research process that you can trust no matter what the macro market does. There's always going to be crazy stuff going on. It's the nature of our world. They're going to make stuff up if they have to. If there's not a war, if there's not some terrible virus, they're going to be making stuff up. They're trying to get your attention. That's how they monetize you. So, you're going to need something that can help you navigate through these constant storms, these constant assaults of bad information. Because you can't control when crazy things happen. No one can control macro events in geopolitics or headlines or market rotations in fads. And by fads, AI stocks are great, software stocks are bad, and vice versa. It bounces back and forth. Energy stocks are great, financial stocks are great, then they're bad. These things are going to happen. These crosscurrents are inevitable. You want something that can navigate you through all of these storms. and assault of bad information. Because you can control— this is your opportunity to learn how to control your research quality and your investment process. And right now, we've noticed the AI revolution has a truth problem. General-purpose AI sounds incredibly smart while still giving you answers built on weak, outdated, or unverifiable inputs. We've been beating this drum for a long time. You've seen us do an entire webinar on this about how AI lies to you because it is trained on the wrong stuff. It's pulling it off the internet, so it's getting blog posts, news summaries, scraped websites, social takes. It admits that it knows the data is bad, and that fails investors because This AI has no ability to discern the good from the bad data. There's no forensic accounting, no disciplined ratings framework, no traceability to source data. Our approach started with building a superior dataset and a system for translating messy disclosures into standardized insightful metrics. We started with the hard part first, which is why we could bring Google in to pay us. To build an AI agent. The result of what we've done is a system that drives novel alpha for investors of all types. You don't even have to take our word for it. Proof is in our performance. Our stock picking has beaten 16,000 professional buy-side investors to claim the number one spot in multiple categories for over 5 years. Folks, we've been ranked number one in at least one category Typically multiple categories. Straight from the site right there. Months in a row. We've been vetted and validated by prestigious institutions such as Harvard Business School, MIT Sloan School of Management, Ernst Young, the Journal of Financial Economics. Even better, let's go with live market performance. How about actively traded indices Run by Bloomberg, the Core Earnings Leaders Index beat the S&P 500 by 900 basis points, 27/2025 alone. It's beaten the S&P 500 by 40% over the last 5 years. The Very Attractive Stocks Index— this just holds all the stocks that get our very attractive rating, that's it, super simple— it's beaten the S&P by 18%. Over the last five years, and perhaps my favorite, the core earnings weighted S&P 500—an enhanced S&P 500 product. We don't even have to pick the stocks. We let the S&P 500 pick the stocks. We weight them more intelligently. That's outperformed by 25% over the last five years. As I mentioned a minute ago, Google chose us to build an AI agent. They chose our data. This is straight from the press release. New Constructs' proprietary data and ontology marries deep subject matter expertise with advanced AI capabilities. Why did Google invest $2 million in us to build this agent? Because they wanted access to the data. Because when you actually marry good data with AI technology, you get something special. Remember, anyone can claim they have the best research tools for stock picking. And many other publishers make this claim. However, we have the proof that our research outperforms the market. Now, I'm going to pause here for just a second. I want this to settle in. Do you have any questions about how our data, our research, and our ratings are proven superior to everything else in the marketplace? Is there any more proof that we could possibly provide? Do you know of any other firm that is anywhere close to this? Even one piece of this performance of the index, stock picking rankings, validation by Google, papers written. 4 things, 4 independent validation elements. Do you know anyone else? What more could you ask for? from a firm that's asking for your trust. We're in a very narrow window right now, especially with geopolitical inflation and midterm uncertainties. Things are nuts and it's only gonna get worse. Every investor wants to address problems before they hurt their portfolio. When you know you got 'em coming at you like crazy, you know you need to gird your portfolio quickly, soon, before the market knows. You wanna find alpha in the stock market. What does that mean? You need to understand what's gonna happen before it happens. You need an edge. If you're not prepared, though, you're going to be caught flat-footed. That's the alternative. If you're not doing the work, or you don't have someone that can do the work and do the diligence, you'll be caught flat-footed, outmaneuvered by Wall Street and other insiders. But if you have the right tools and the right analysis, you can anticipate, you can position yourself. Before the market catches on. That's how you outperform. That's how we outperform. That's the real opportunity. That's how the smart money does it. Lately, investors are turning to AI all too often to try and find the right tool. All the generic AI firms are touting that their AI is so powerful it could take over the world or hack governments, right? That's how they scare you into thinking, oh, this AI is so amazing. That's what they want to talk about. Let's bring back Skynet. Let's talk about how Anthropic AI can't even be released to the public because it's so powerful. That's wild hype to cover the fact that generic AI is really weak in many areas. There are some places it's strong, stronger, but super weak in many areas. Specifically, most AI tools are nearly useless for investing. They only can summarize the internet. They're not designed for, for financial analysis, built on inconsistent, incorrect data. Result? They pick what's popular. Popular does not equal good. Popular is by definition popular because people are paying attention. That doesn't do you any good. You can get that anywhere. It's not hard to find what's popular precisely because it's popular. So let's understand. What the problem is here. General LLMs are designed to summarize lots of data from lots of sources. They are not designed to discern or be financial truth engines. We've proven that many times in prior trainings, and you can prove it yourself by asking any AI you've worked with, why does AI lie so much? Try that prompt. Here's another thing that we're seeing emerge now more and more, Is this understanding, this, this truth narrative from Larry Ellison, one of the most successful technology people in the history of the world, is saying the same thing that I've been saying, that all these frontier models, generic AI models, they're all using the same internet data. They're converging. That's why they're saying the same stuff over and over, because they're all using the same internet data. Now we're starting to see what I predicted years ago. Back in 2018, I said it's all about the data, proprietary data ontologies. That's what's going to make the difference. And we're seeing it happen right now. Apple suing OpenAI for stealing their data. Now we're not just talking about data centers and power and compute, which is something people can actually acquire and build. The hard part is getting the data right, and they know that, which is why they don't talk about that. But the problem is that users are now switching to lower-cost Chinese AI. Why not? If everyone's just going to use the internet, then basically all the models are the same. Isn't that what Larry's saying? So why would I pay 10 times more for ChatGPT or Anthropic or Gemini when I get something just as good from China? Now let's go through this exercise. Let's explore what the popular AI tools analysis of the tech sector says. We asked 3 different AI tools, what are the best tech stocks? Here's what we got from ChatGPT. Here's what we got from Gemini. Here's what we got from Claude. We noticed a few things. First, none of the listed stocks get our attractive rating. We don't think any of those are good stocks. Second, there's no fundamental research or solid data to back them. Third, they're all doing the same thing. Looking at past performance and market cap, stocks that perform well and are big. Not exactly what I would call brilliant insight. Please keep in mind, our AI agent and stock picks are proven to outperform the market consistently. Proven. So we can confidently state we know how to determine whether a stock is truly an attractive buy or not. Proof is in performance, folks. Again, I'll pause here for a second to see if any questions or concerns around why our research is proven to work. And if you know any other firm who can say the same thing, open to hear it. However, we've noticed the free AI tools such as ChatGPT, Perplexity, or Claude tend to select stocks that are popular, big-name mega-cap stocks, often overvalued companies that have already experienced large gains. They are not attractive right now. It's old news. We've got an interesting question in the chat here. What kind of returns on average can I expect using your AI? Nothing. We're not here to guarantee returns. It's illegal to even say that you can do that. I don't know how Cathie Wood gets away with that. If I could predict the future and guarantee returns, We'd be doing this on my yacht. I can help you make smarter decisions. I can't predict what's going to happen in the stock market. I can give you the best possible tool to make the best risk-reward decisions about US stocks. So there's no guarantees here, folks. No guarantees in life. There are no free lunches. What I can tell you is I can help you make the most informed decision, which is the limit of what can be done. for smart investors. And telling you what's popular is not adding value. That's not giving you good information for risk-reward. Popular is the easiest way, but not usually the best way to do anything. So where most companies are going wrong with AI is they pay too little attention to the inputs, folks. All the focus is on fancy outputs and huge data center spending. It's a cover-up to the most important universal rule for modeling. And that's garbage in, garbage out. As long as they're talking about, oh, how they're spending tens, hundreds, billions, trillions of dollars on data centers, you know what they're not talking about? How they don't have any good data to put into those systems. So how do we build our system? We started with what matters most. We started with good data because we know models are going to come and go. High-quality data has enduring value. So we start with the superior inputs and data. We add an ontology that truly converts that data into alpha-generating signals. Clean data, good models gives you real insights. Here's how it looks, folks. This is one of my favorite slides ever. Anybody can look at financial statements. That's not hard. Even a monkey can do that. Now you got to have a smarter monkey to read footnotes, a really smart monkey for that matter. It's a significant improvement over financial statements, but it's not enough. You got to do financial modeling and know how to put all this data together into an ontology, which is really what we're talking about here is ontology. And then you can get novel alpha like the Core Earnings Leaders Index. And once you've got the system in place to do that, get you Finsights. That's our AI. That's real AI built on proven superior intelligence and research. We spent 20 years building this truth engine. Our proprietary RoboAnalyst was built for one purpose, to build the truth engine, to go through the filings, to do the dirty work, the difficult work, which, by the way, I believe machines are better at than humans, certainly at scale. Correct the distortions. We're discerning. Our machine was built on discernment. We had expert humans going in and discerning the differences between accounting line items that look the same but mean different things, or look different and mean the same thing. 43 billion times. That's what you call a training dataset. That's what it takes to teach an AI to do something spectacular like what we could do. We adjust for off-balance sheet debt, unusual gains and expenses better than anybody in the world. We calculate true recurring cash flows better than anybody in the world. The result? We convert misleading reported results into true economic reality. That's how you pick stocks better than other folks. That's how you beat the market. And we're not a black box. Every metric we provide, every rating we provide is 100% transparent. We'll show you the formulas. We'll actually show you how to get to the source data. Why do you think Bloomberg, Google, Harvard Business School, MIT Sloan— academics don't just work with anybody. They're going to risk their reputation. They're going to audit it back to the source. They can do that with us. And the reason you don't see any other research firm that can make a comparable claim, because they don't have the auditability. And if you're not willing to show how you did it, what does that mean about how you did it? Why would you hide it if you could be proud of it? Our clients can audit every single data point back to the original source. Here's how it looks. You want to know where we got that restructuring charge? How about page 100, deep in the footnotes? How about page 113, deep in the footnotes? Here's another thing that matters a lot, folks, is we're 100% independent. We're not paid by companies. No investment banking conflicts. Now let me share 3 key ways our clients leverage our tools to pick the right stocks. Number 1, the freshest data. Daily updates for 3,300+ company models with the latest financial data. As soon as the filing comes in, we're going to analyze it, usually within 24 to 48 hours at the most. We take the daily download from the SEC every night, we process it overnight, We— our analysts do the review and checks in the morning, then we do a batch update that evening. The model updates drive our stock ratings, which is why we update them on a regular basis. Every time a new filing comes in, we get filings pretty much every day. Now, they tend to come in big bunches, though, during propaganda season or filing season, which is right after earnings season. And they— those filings drive lots of changes. And ratings changes are really good at identifying winners and losers. And we've shown empirically how rating changes, stocks move. Here's an example. Motor Car Parts of America, we upgraded from neutral to attractive in February of last year, right after we parsed the 10-K. Over the next month, it was up 60%. Dell Technologies, got the filing, upgraded the stock, up 32% in the next month. Second thing about what makes New Constructs special, we have the best data. Our clients get the most rigorous fundamental analysis in the world. I would suggest that every company model and report on an individual company, like if you're a pro client, especially if you're an institutional client, you're seeing one of our full models. If you as an individual on the street wanted to hire someone, they're going to charge $50,000 for that because that's how much time and work it would take. And from an expert, they're not going to be cheap with their time. That's how valuable it is. That's how hard it is. If you wanted to get 20 years of data, 15 years of quarterly data in there too, that's just— and then all of the adjustments and the model to make it work and the screening tools and the ratings and all that to give you that kind of— to replicate what we do on one company, super difficult. That's why no one else has done it, my friends. No one else has done it, as we've proven. This consistency, this kind of work that we do all the time, means that you're getting results you can trust across thousands of stocks. To give you context of how our proprietary research scales, let's bring up Warren Buffett. In this article, they estimate that he's read about 100,000 financial statements in his 70-plus career. Over the last 20 years, we've looked at over 250,000. And counting. That's the human expert validated stuff. That's what drives the 43 billion data points that informs our AI. So it's fair to say New Constructs has analyzed 2.5 times as many financial statements as Mr. Buffett and counting. That doesn't count the AI training itself, in which case we're in the millions. Third, Benefit to new constructs. Trust. We maintain true independence. We have no investment banking or other conflicts, just pure, honest research that works. And the proof, folks, is in our stock picking and in our ratings. As I mentioned just a second ago, our ratings make a difference. Less than 4% of stocks in our 3,300+ coverage universe get a very attractive rating. Less than 13% get very attractive or attractive. Whereas on Wall Street, 96% is buy and hold, my friends. 96%. Crazy. That's because their paychecks depend on you buying stocks. They don't make any profit in the research department, right? I've told you that before. What percentage of revenues come from the research department, folks? Anybody know? 0%. What percentage come from investment banking? Big difference. Investment bankers make a lot of money. Research departments don't make any money. So if you don't help the investment bankers make money, what happens to you? According to recent data, 50% of Wall Street ratings for stocks are listed as buy compared to our 13%. Again, why is that? Because they get paid to sell stock, and it's really difficult to get a company to let you to pay you to sell stock if you don't say good things about them. I've seen it happen. One of my best friends in the Wall Street business, been one of the top research analysts on banks of all time, Mike Mayo. Just saw him in New York a few weeks ago. Great guy, did great work always. Been fired once or twice. He— I remember it was happening at Credit Suisse. Fired because he was not positive enough on banks. Now, the value of our AI solution— I want to talk to you about this— is proven by our performance. This 20-year journey and this foundation of audited superior data has led us to this moment, folks, to give you an AI that really works. We call it the $2 million edge because Google chose us and invested over $2 million to build what we're revealing today. They don't do that for no good reason. They do that because the hard part was never the AI. The hard part is finding accurate data. We're seeing this play out right now under our— right under our nose. FinCEN's AI. Google chose new constructs because they understood a core truth about machine learning: garbage in equals garbage out. From the press release. New Constructs' proprietary data and ontology marries deep subject matter expertise with advanced AI capabilities. From my friend Brad Little, Global Head of Professional Services at Google Cloud. Also from the press release, AI can be a direct engine for advances in intelligent investing when it's powered by high-quality data. From the Global Head of Professional Services at Google Cloud in the press release about Finsights, folks. Again, tell me where you're going to find greater validation than that. Finsights can be your truth engine for the stock market. Core function: have a conversation with our entire database. You can ask it plain English questions and get reliable, verifiable answers in seconds. Let me give you some examples. Here we are with what are the best stocks in the industrial sector ranked by overall rating. Bam! 10 best stocks in the industrial sector. It's not going to give you database reports. We couldn't let you come in and say, hey, FinCites, will you download all the New York New Constructs data? Can't do that. So it's going to give you pieces of it, but you can still get tons of data with the subscription. You're going to get data close to the level of what even pro and institutional people can get. Not quite at their scale, but in bits and pieces you get there. How about this? Which stocks in my portfolio are most likely to miss earnings? Here you go. Street earnings, street earnings distortion score. Street earnings distortion. You can see which ones of these stocks in the portfolio have the worst earnings distortion. Earnings distortion being how much they're overstated. In seconds. Show me the stocks in the US 500. That's the term we use for S&P 500 because we're not a licensed licensee of S&P 500, so we don't talk about it or publish it. We call it the US 500. Show me the stocks in the US 500 with the worst combination of high gap score and low ROIC. There it is. Here are the top stocks in the S&P 500 with the worst combination of growth appreciation score and return on invested capital rating. There's the result. How about another question? Which stocks in the healthcare sector have the highest earnings distortion? Bam, there it is. Show what is the worst sector right now. Show me average GAAP score, average price to economic book value, and average ROIC for all 11 sectors in a table. There it is. Show me the sector with the most stocks rated very attractive right now. Which sector has the most opportunity? There it is. Find potential short candidates. Give me the stocks in the US 500 rated 4 or 5 with the worst combination of ROIC, free cash flow yield, gap in price to economic book value, broken down by sector. Rank them accordingly and show in a chart. These are my short candidates. There you go. Short candidates and what sector they're in. Pretty cool. There's charts for you. So the real advantage on this, honestly, folks, the key is that you can go in and get pro-level data and the answers to your questions. Which stocks reporting earnings this quarter have the largest gap between Wall Street's earnings estimates and what their core earnings trend implies? Show me the biggest disconnects. There we go. That's the earnings capture ratio there again in the 2000s. Understated. Distortion per share. Huge numbers here. When you're looking at a huge database like we are, you're going to see crazy anomalous numbers, folks. Like, for example, recently for a partner, we're finding balance sheets that don't balance. Can you believe that in today's day and age? Balance sheets that don't balance. We see everything, folks. Show the difference between core earnings and net income for the US 500 since 2010. There it is. Most of the time, core earnings is better. Every now and then, not so much. Remember what happened in these periods? Pretty interesting. Of course, the screenshots we posted represents a small fraction of its true potential. We wanted to give you real examples. But the possibilities are truly endless with what you can ask FinSight's AI.

Other examples.

Of great questions. What are the highest rated stocks in the software industry? What is the most profitable energy company? Which healthcare stocks or which healthcare stock has the best economic earnings? Show me the cheapest stocks in the tech sector. What are the highest dividend stocks in any sector? Health, financial, industrial. Show me the most attractive stocks in any sector. Which sector has the most very attractive stocks? Which sector has the most very unattractive stocks? Show me the most dangerous stocks in the market. Show me the most unattractive stocks in any given sector. And you know you can trust the answers because they're from the same data that's been proven to outperform the market, folks. That's the difference. That's why I spent all that time on Harvard Business School, MIT Sloan, Bloomberg. Google, the Journal of Financial Economics. That's why I pause there, because I want to talk to you about the foundation, the inputs. Garbage in, garbage out. Gold in, gold out. That's why you can trust us. And I look, I don't take the word trust lightly. Trust is probably the single most important thing in all of society. It's what keeps us together. It's what keeps us moving forward. You don't have trust, I say ditch it and move on. But if you find something you can trust, it's invaluable. Now you're probably wondering, how do you get access to our research in FinSights AI? For years, our research has been available to institutions, hedge funds managers, large asset managers, institutional investors, and they pay $12,000 a month for this kind of stuff, for obvious reasons, folks. Then We made things more accessible with our flagship professional membership. But even at $999 a month, even that is a bit out of reach for most individual investors. We do have a lot that have to take access to that professional membership because they want that power. But we realize a lot of you have smaller portfolios. We needed to do better. So we asked ourselves, what if we can make institutional-grade research accessible to individual investors at a price that makes sense to individual investors? Today, I'm excited to announce the answer: Discovery Plus Finsights AI Bundle, designed specifically for investors who want institutional-grade research tools but don't need every single feature that comes with our professional and institutional memberships. Perfect for those with smaller portfolios who don't want to be overwhelmed with every single data point describing everything that goes on. With Discovery, you get ratings on 10,000 stocks, ETFs, and mutual funds, tracking up to 50 securities in your portfolio, alerts anytime something changes for any ticker in your portfolio, monthly video podcasts with me, access to a vast library of MBA-level education materials. Access to a vast library of Wall Street propaganda-busting materials. Plus you get screening of our universe of 10,000 stocks, ETFs, and mutual funds based on the rating, the market cap, the price, the dividend yield, sector, and industry. You're not getting every single data point to screen on, but you get the rating, and the rating is based on every single data point. Same is true for ETFs and mutual funds. You can screen by rating, type, price. An amazing tool for scanning the entire market. And of course, you're also going to get FinSights AI, our new AI agent built to deliver you the $2 million edge. Go ahead and click the link in the chat we provided and get access. Quick question, does FinSights AI perform Stock valuations, that will give me a rough idea of entry and exit points if I'm investing in stock. We provide risk-reward analysis, and it includes— and I'll show you in a second— both valuation and fundamental analysis. Remember, the nature of our research entails countless pages of data and documentation, including information from balance sheets, income statements, cash flow statements, footnotes. It is 43 billion data points, my friends. That's what it takes to drive a real AI. What do you need? You need insights. And by understanding the true profitability and identifying the hidden risk, we can build a superior financial model to find the best stocks, to give you insights based on those 43 billion data points. Our stock ratings are grounded in the verifiable numbers from the filings, not speculative narratives. Popularity contest or biased analyst reports. This gives you a much more accurate picture of the company's sustainable profits and helps discover, discover stocks such as Mind Technology. We got the 10-K, parsed it, upgraded the stock up 32% in the next month. Alibaba, parse the 10-K, That drove an upgrade to the stock, up 24% in the next month. You think institutions are paying attention to this? I think so, because they can save billions with just one good avoidance recommendation. And by the way, our avoidance recommendations just as good as our buy recommendations. Caesarstone downgraded from neutral to attractive. After we got its new 10-K, down 24% in the next month. Voyager Therapeutics, we parsed the 10-K, down 22% in the next month. Our Discovery and Finsights AI membership provides unrivaled insights about the thousands of stocks in the US market and thousands of ETFs and mutual funds as well, all based on research proven to generate alpha. And vetted by top institutions, folks. I implore you, find another research firm with our track record and independent validation. Producing and maintaining this level of detailed research would set people back millions of dollars. That's why they don't do it, folks. Some of my best clients have actually said, yeah, David, you know what, a 20% price increase, I don't mind because you're saving me millions of dollars to try and replicate what you do. And the membership gives you access to a level of depth of financial research that's considered a gold mine to these folks, my friends. This offer gives you access to a gold mine, and it consists of superior unbiased ratings on 10,000+ securities, portfolio tracking— type in all your tickers and get a rating on every element of the company's profitability and valuation. Stock screening with an unrivaled level of precision. You go through the whole market and identify all the stocks that get a very attractive or very unattractive rating in seconds. Incredibly powerful tool. Alerts to anything that you're holding and paying attention to. Alert on the 50 top stocks, ETFs, or mutual funds that you care most about. Yeah, we can do that. With— and the takeaway here is that with Discovery plus FinSight's AI, You can invest with confidence knowing you have access to the most accurate research and ratings available on fundamentals. Maximize your profit potential with decisions informed by proven superior fundamental data. Leverage our AI to thrive in any market condition. Enjoy real due diligence. Have the peace of mind of knowing that you get the complete financial picture when making financial decisions for yourself or for your clients. And of course, you also get access to FinSight's AI with our special bundle. So you're probably wondering, what's the price of the Discovery and FinSight's AI membership? Let me first tell you what it would cost for you to do it on your own. $2.7 million just to analyze one quarter's worth Well, that's what we estimate, assuming you're paying somebody about $100 an hour to do this kind of work. Every filing's about 8 hours. The typical novel, 200 pages, people estimate— you can look that up— how long does it take to read the typical novel? About 200 pages. Estimate 8 hours. Filings are about, on average, 200 pages. I think they're a lot more complex than a novel, a lot more legalese, financial jargon in there. But we're being conservative. If you assume 8 hours per filing, this is what it would take if you charge somebody— if someone charged you $100 an hour, $2.7 million for one quarter. We've got up to 20 years of history back to 1998 for a lot of companies. And that's why our high-level clients— here it is. This is straight from the, straight from the bank statement, folks. However, we're not asking you to pay $12,000, $5,000, or even $1,000 per month. How about some more use cases? Of these 5 stocks, which has the highest return on invested capital? Apple, Nvidia, Google, Microsoft? The answer? Nvidia. Now folks, I want to just take a quick second here. Our measure of return on invested capital— Ernst Young published an entire paper talking about how we measure that better than anyone else. Warren Buffett has said over the years, the single most important measure of a company's performance is return on invested capital. We give you the most important measure of profitability for companies on thousands of stocks better than anyone else. And FinCites can give you this kind of analysis in a heartbeat. And by the way, it's going to be really important to know this number because a lot of these AI stocks are going to be blowing up in the not too distant future. More examples of use cases. Show me the cheapest stocks in the tech sector based on economic book value. Bam, there it is. So what I want to make sure, folks, you understand is that this is really special because individuals usually don't have access to an entire research department and dedicated analysts, machine-scale parsing tools, institutional screening power. You don't get access. You don't have that. Our Discovery Plus FinSights membership, we close that gap, folks. We give you access to an entire research department. I would argue that it's better than the entire research department for Morgan Stanley. Why? We cover more stocks. We also are independent. We're not getting paid by bankers. That's 2 reasons why our research is better than Morgan Stanley. Goldman Sachs, Bank of America, you name them. All of them together, we're better. We cover more companies. We do it with more honesty. So let me ask you, I've been doing a lot of talking. We've got a few questions in there. How about you guys pay me the one small favor here for this training today? Can you explain to me why you should settle for anything less than new constructs and this Discovery plus Vincite's AI agent? I'll drop the mic here. Why would you settle for anything less? Crickets. Seriously, why would you settle for anything less? There is no reason to settle, not when we can make available at this incredibly low price such a powerful tool. We are giving serious investors access to a superior core earnings research engine, rating system, and screening ability. Period. How about a few testimonials from some of our clients? Along with your integrity, we appreciate your commitment to maintaining high standards and your courage for saying so. I would please throw into the chat or the Q&A any other research firm that's got quotes as good as this. It just doesn't get any better than that for me anyway, because that's what I care about most is integrity, doing things the right way. From Joe, simply and instantly you can see how your stocks or funds are rated and where they are trading compared to economic book value. The top-down view is incredibly useful. I highly endorse the new construct system as one must-have in any stock or fund selection system. Folks, we're not saying new constructs needs to be 100% of what you should do, but it shouldn't be zero. This is from Chris. She talks about how she's been using new constructs for years to manage a portfolio that supports her and her husband. And she says, I sincerely appreciate all the work that has gone into creating this database. Going from marked-up footnotes to filings— in filings— to reliable, easy-to-understand indicators of a company's performance is a huge undertaking and deserves my utmost respect. I find your information to be reliable, relevant, and trustworthy. New Constructs is the only company that has allowed me to feel secure in both my buy and sell decisions, and that has been truly valuable. I expect to continue using New Constructs throughout my life. To avoid ever running out of money. Folks, that's trust. Now, not blind trust, right? They say trust but verify, and I think we provided an enormous amount of verification. It can— it provides me with concise insights into investment opportunities derived from meaningful metrics that I couldn't duplicate on my own. Folks, this is important. What we're doing is important because trust is on decline. And that's not good. We can suffer it for a little while, but if it moves too far in the wrong direction, society will suffer. The world will suffer. All those dystopian sci-fi movies, that's what happens when we lose too much trust. And folks, it's getting bad. And that's a big part of why I wanted to create New Constructs to begin with. I wanted to give people a place they could trust because trust is absolutely essential. It's the oil, it's the gears, it's the engine. It's all these things for our capital markets. We lose trust in the capital markets, we lose the advantage that makes the world improve its prosperity more than anything else. And the new constructs— hey, I am all about trust and transparency. I'm not asking you to trust me blindly. I'm going to trust and I'm going to give you verification. I remember when we first built in that click-through feature that showed you the trace way back to the filings. And my team was like, what? People really want to see that? Yes, we need to share that. And that has become a defining feature of what we do. Harvard Business School professors, one of the first things they did, show me. Bloomberg, show me. Google, show me. Clients, show me. Two Sigma, show me. GSAM, show me. We can show— we can also show pretty incredible performance because we do it for the right reasons, not because we're compensated to promote. We do it for the right reasons because we believe truth, honesty is its own best reward. Why now? Why do you need this now? Because misinformation is at an all-time high. AI adoption is rising, and you need AI. You need something to help you deal with all this noise. And you can't trust generic AI. You need better tools. And FinSight's AI is better and at a way better price. Go ahead and click the link in the chat that we provided. You can sign up right away. Alright. Let's do a live demo time. This is the best part. Alright. Anybody got any particular prompts you want me to try? Thanks, Andrew, for putting in some examples of great results. Folks, if you're not seeing in the chat here, We've got look there's nothing better than live live testimonials going on for how well the system works. You can see here from Andrew and somebody asked him, Andrew, can you define great results? And here he is, a couple of examples right there. Yeah, here's except I'm gonna say okay, will you put the core earnings results for MSFT into a Line chart, please. I treat AI with respect even though AI probably doesn't even notice. But I, I just sit in such the habit of saying please and thank you because my grandparents hammered me on that my whole life or my early life. And I've never heard anybody say it's a bad thing. So I figure, yeah, apply to my AI. Maybe it'll treat me better. I'm gonna show you another feature here that's really cool because this is our discovery membership. So if I were to open another screen here and you go to the members page, This is a brand new AI membership. You can see nothing's in here. If you wanted to add tickers that you are most interested in, you would type them in, or you could copy and paste a list of tickers in and you get it. Boom. There you get the ratings and on all the details. If you wanted more details on the rating, click here and see how all that works. Kyle, how's it going on your side?

I did run through a whole bunch of questions as we were going through the presentation.

Why don't you share your screen?

So we had some prompts in the presentation. Here's things you could ask it. And so I was running through each of those questions. What are the highest rated stocks in the software industry? You get your list here. It's telling you how it defines highest rated stocks there. What's the most profitable energy company? It's going to pull out and tell you exactly why it's pulling those results. Which healthcare stock has the best economic earnings? And so I was just going through that list of Cheapest stocks in the tech sector. So all the different ways you can get info from the system that you might not be able to quickly find on your own because you have to scroll through the entire screener list or find the highest dividend stocks. You got to go and get each individual one. Most attractive stocks financial sector. There's a whole bunch of different ones. Most dangerous stocks in the market. Anyone looking for stuff to watch out for? Very unattractive ratings there. And then let's see what stocks. Most likely to miss earnings.

Let me share that while you're looking at that. Perfect. Yeah, here we go. All right, there's a line chart. So I will tell you that when we were building this thing with Google, there were days that we would wake up and stuff that we tested the day before and was working great wouldn't work. And I finally had to tell the Google people because I'm like, listen, man, Wasting my time. And I went to the boss. I was like, they're wasting my time, dude. This stuff works right there. And they came back and said, it's not our fault. We don't know what's going on. What are you talking about? In the beginning, they were all building their own sort of separate AI tools at Google, different groups. Then they decided to centralize that effort into one group. They took the all-stars from all the other groups and they had one group. And it makes sense, right? We're gonna have one model to do all of AI. The problem is that the group making those changes doesn't telegraph what those changes are. They just make changes, push 'em out. So a feature that's working one day might not work the next. And I was like, are you kidding me? You can't ask me to test this thing. I can't keep pushing the rock up the hill over and over again. So they created a system that they added back to their own AI that would check for that kind of stuff so that people would know, hey, is it a problem with what I've built or what the core AI has built? And I'm telling you folks, with the new constructs, there's no problem with what we built. Our AI is all about new constructs. It's not going to pull crazy stuff and hallucinate from the internet. It's not going to infer anything. It's not allowed to. It pulls from our data. It allows you to access the database in a cleaner, quicker way. And by the way, you can download this. Click this button, Microsoft Core Earnings Over Time, in a chart you could put into your own research if you wanted to. Here's another chart it put— it created the other day, a very interesting analysis of the difference between core earnings and reported earnings. That did a line chart for me yesterday. I forgot I downloaded this. I was actually testing the new download feature. So that's another cool example of what you can do there. Any questions or suggested prompts before we close out this presentation?

We've got some common questions in these slides if you want to go through those real quick, David.

Yeah, we'll hit that. So common questions. As a first-time user, how can you be sure you're going to know how to use it? First of all, it's designed to be simple. I showed you in just a few seconds the screening tool. The portfolio tracking tool, the ratings. Green is good, red is bad. We're not here to be complicated. We're here to simplify complexity for you. That's what we call value add. Secondly, we've got tons of tutorials and trainings that show you how to get the most out of Discovery Membership. So we'll guide you through it. You can also book a demo with us anytime and we'll show you how to work it. And there's a big button on our site about booking demos. Common question number 2, are the attractive and very attractive stocks identified with the Discovery Plus Finsights AI bundle Guaranteed to have a double or triple-digit gain in the next year? No. As I said earlier, folks, we're not doing any guarantees here. If we could guarantee anything, we'd be doing this on my yacht or my jet. The best thing you can do is position yourself for the best risk-reward, and we do that better than anyone else. But no, there are no guarantees. What can I actually ask FinCites AI? Great question. The answer here is broad. Anything you would ask a human analyst in the course of evaluating a stock, a sector, a portfolio, or a fund. We'll give you a prompt guide that gives you some very specific examples. But it's basically everything about new constructs. Now, you can't ask it to give you the formula for Viagra. It doesn't know any of that stuff. It's not going to know anything about pharmaceuticals or technical research. It's going to know about new constructs, the best fundamental research in the world, And we believe that's the way to build AI on a small language model. One language you got exactly right and that you can trust for building deterministic rules because it's got a track record of generating alpha and outperforming the market. How many questions can I ask FinSights AI? Do you get an unlimited number? No, you do not. Do unused tokens roll over? They do not. You get a specific allotment every month. You get about 50 questions. It depends on how complex they are. Some questions are cheap. Some questions are more expensive depending on how complex they are. And if you want more, you can always buy more tokens. It's super cheap. It's super cheap compared to the $50,000 you'd have to pay an analyst to build a model. How is Discovery different from the Stock Tracker membership? Great question. Discovery includes everything in Stock Tracker. Plus screening capabilities. And I think the screening capability is amazing. To be able to instantly and effortlessly sort the entire market— stocks, ETFs, and mutual funds— by the best and the worst— amazing. Doesn't get any better than that. You get more robust tools designed for investors who want to avoid paying for features they don't need, which is access to underlying data, reports, filings, And of course, you get access to Finsight's AI that is not available with Stock Tracker. Only with Discovery and above can you get Finsight's AI. Any other questions before we close up here? Does it provide institutional dollars moving in or out of a stock? We do not track money flows, but we do know of a firm that does that very well. It's called Exponential Tech, run by my good friend Morgan Slade. And yeah, he is an ex-Citadel guy and he was there when they were creating and tracking money flows. And he's taken that technology and capability and he's created this new firm called Exponential Tech. And it's doing extremely well. Doing extremely well. And yes, they will give you institutional and retail money flows, which is, I think, a super valuable capability. And yeah, I think it potentially is super complementary to what New Constructs does as well. Any other questions? Kyle, did I miss anything in the chat or anywhere else?

Nope. I think that's it.

Awesome. Alright, folks, thank you very much. I'll leave you with 3 things. There's nobody you can trust more. There's nobody has more verification, and there's no better AI in the world. And I challenge you, why would you settle for anything less? Thanks and have a great day.