Good afternoon. Our final presenting company of the first day of the IDEAS Conference is Research Solutions. Trades under the ticker RSSS on the Nasdaq. Company plays a key part in the research process, helping to collaborate with researchers, making their time more efficient, and saving their research dollars for better use.
Here today to present on behalf of the company is Josh Nicholson, Chief Strategy Officer, and with him is Dave Kutil, Chief Financial Officer. Josh?
Thank you. Kutil, right? I learned that on the last earning call now, I'm always like catching it myself.
I always get Because there's no C CC .
No. Yeah.
Kutil.
All right. Thanks, everyone, for coming. I know we're between happy hour. Maybe you guys are excited to go out and experience some of the mayhem. For me, I'm actually on paternity leave, I'm on my fifth cup of coffee or sixth cup of coffee of this day, but I'm really riding the lightning.
Today, I'm going to talk a little bit about Research Solutions, what it is we do, why we do it, what is the business and why is this a good investment opportunity. I am a researcher by training. I finished a PhD back in 2015, studying cell biology. To me, research is amazing, right? It gives us the ability to get out of pandemics. It gives us the ability to create amazing technologies.
We're truly living in a time unlike any other time. This starts with research. It is a huge market. It encompasses everything you can think about. I like to say there's research on Peppa Pig, how that influences kids learning English. There's research on prostate cancer. There's particle physics. Nearly anything you can think of, there's a research paper.
With that said, it is challenging to keep up with research. There's a lot of research that's coming out every single minute, it's hard to trust, right? There has been studies over the years looking at reproducibility of literature, in that how much can we reproduce, how much can we just copy what has already been published to validate to make drugs or to build off of this.
We started Scite, which is one product under the Research Solutions umbrella, back in 2018, really in response to growing concerns around reproducibility and trust. As we talk about it, trust is paramount, right? We're all using AI. How do we trust it? I think we hold some pretty unique data and some pretty unique way of looking at that data that is really important in the world of AI.
I think it's important to remember that research is, yes, it's this thing us nerds do, but it's also giving us all these amazing things that allow us day to day to really live where we're living today. That, I think, with research, with AI, can really multiply the R&D output. We've seen some amazing advances with that, predicting protein structures with AlphaFold.
We're starting to see some big acquisitions from companies looking at life sciences, I think that is really the next frontier of a lot of these AI companies is going from tech to life sciences, where the challenges are exorbitantly harder, right? There's a saying, one cancer smarter than a thousand cancer researchers, I think that's true.
I think AI is really going to help multiply our output, I think we're well positioned for that increase. The AI as it is today falls short, right? ChatGPT, you can ask it any question you want. You can give it any prompt. It's going to give you an answer very confidently. We all have seen that it hallucinates, right? This is a word, I don't know if you search the Ngrams, hallucinations would probably rise. That is a big challenge, right? The trust of this.
How do we know that this is an answer that we can use, whether that's related to a question on finance, related to a question on cancer research, et cetera. From the left, you see a researcher. It's making up things, right? It's gotten better. ChatGPT started referencing no webpages. Now it references webpages, but it still is referencing the web.
In research, the web, a blog post is very different from a peer-reviewed article with statistics, with evidence, et cetera. These AI tools, as amazing as they are missing a key component, and that is really research articles. Our articles enable research in the era of AI. That is the ability to get answers as well as the ability to get access. That's how I bucket, I would say, our two core products, Scite and Article Galaxy.
Scite is, as the name suggests, a next-generation citation tool. What does that mean? We have spent almost 10 years partnering with publishers, getting AI agreements to the full text of scientific articles. You can ask a question. You get an answer directly from the full text of scientific literature.
This is, in my mind, answers, right? We, again, have been signing AI agreements before ChatGPT existed. We were Scite.ai since 2018. We recently sold to Research Solutions about two years ago to join Article Galaxy. Article Galaxy is access. Article Galaxy is used by most major corporations in the R&D, so large pharmas of the world, and we'll break down customers by segment later, to get access.
If you are an AstraZeneca of the world, you need one place for your thousands of researchers to buy an article, to access via subscription, to access via tokens, et cetera. They come to Article Galaxy to do that.
A simple way of looking at this is answers. So answers from the literature, citations that can show you supporting or challenging studies, and then access, buying articles, renting articles, or accessing via entitlement, subscriptions, tokens, et cetera. We have recently launched, in addition to our platforms, connectors into the most sophisticated tools. MCP, the Model Context Protocol, is a standard.
There are new app stores effectively in ChatGPT and Claude. We have built our tools in there, and I think we're early there. If you search science on ChatGPT, we are one of the only two tools that would show up, Scite and BioRender.
There's now more there, but we're still early. We've built in these connections that will leverage really our unique aspects in the tools where people are living. These are the fastest-growing tools ever.
The strategy that we've taken is to go to where the users are, recognize our differentiators, which is access to research articles, quality signals for research articles, and then the ability to buy or access articles in these tools.
You can go to ChatGPT, you can ask a scientific question. It's going to use the web. It might even be blocked from the open web. If you use our Scite connector, which we had actually one investor do today while we were talking. It will then go search the full text of the literature. It'll give you answers.
It will tell you if that study's been supported, if it's been challenged. Then you can buy it directly in the tool. If you're a corporation, you can say, "Hey, it's already in my corporate library. Use this tool." So this bridge between research articles, research content, so patents, FDA filings, anything under this research umbrella, into these tools.
This is new for us, and I think is really exciting because I think while most users live on our platform today, I think in the future, most users are going to live on these tools and use our connectors.
We're starting to see better unit economics, better retention, better across-the-board usage, just because it's so slick. This is the biggest differentiator. So I've referenced this a few times. We have really focused on signing unique AI rights agreements with publishers.
We have about 40 different indexing agreements, meaning we have every single full text article from Wiley, every single full text article from American Chemical Society, from American Medical Association. These are hard to get without spending $50 million. So we partnered with them. We give to get, so we give different analytics, different integrations.
Our badges are actually live on many of their articles, and we've been doing this for quite some time. Our competitors, some of them are trying to follow this, but it gets harder and harder in this day. So this is a big differentiator. ChatGPT does not have access to the full text of Wiley. It doesn't have access to the full text of any of these things. It has access to OA content, and even then, a lot of that OA content's starting to get blocked.
In addition to this, and I've kind of touched upon it, we have a quality signal. It's not enough to know that this article exists. Is that a good article? Has that article been challenged? Has that article been supported? So this was our day one goal, is building out these next-generation citations, kind of like a Rotten Tomatoes for research, or if there's any lawyers in the room, kind of like Shepardizing for science.
So we have gotten full text to build out these next-generation citations, allow you to look at any article, see has it been supported, has it been challenged, and to see how has it been cited. Again, very similar to Rotten Tomatoes. You wouldn't say, "Hey, it's great. It has 100 references in magazines." You'd want to know what those magazines say.
So we have a proprietary signal, and then we have extremely comprehensive access to the research articles that really is unique in this world of AI. It's early innings, but we're starting to see AI adoption across the board. Universities are spending millions of dollars. They're announcing this in their headlines on ChatGPT Enterprise, Anthropic. They already have millions of dollars in subscriptions or their collections holdings.
We need to bridge those gaps. So this, from a product perspective, really relates to us going into these tools. We don't want to compete with ChatGPT. We'd lose. We don't want to compete with Claude. We want to leverage the best of what we have, recognize where we would lose, and then go into them. Make sure that that's a strong sell. So what this looks like, and I'm going to maybe skip this, is this.
This is, I think, it's a lot, but this is where I see us today. There are academic and corporate institutions spending a lot of money on AI. One university is spending $3.5 million a year on Anthropic. Corporations spending as much, if not more. Again, plus or minus a couple million on this. Big AI spend happening in academic. Still early. Not every single university has a ChatGPT Edu, but it's starting to roll out.
Similarly, libraries, corporate and academic, they have big spends on their articles. They need to buy articles. They need to pay subscriptions. These are millions of dollars of subscriptions. Between those exist our two products. Scite, the ability to search those articles, to get answers from those articles. That is unique. Otherwise, they can't interrogate those articles. Then to get access to those articles. "Hey, we've already bought this.
It's in our company library. We can use it." Go ask a question of this, bring this in there. "Oh, hey, this search identified this article." You don't have access. Buy it directly in line in those tools. We're trying to bring what we have done in our platforms directly in line through these connectors, which are now live in ChatGPT and Claude and they're under review in the Copilot store, but they can be used across any of them,
Whether that's an enterprise or whether you're a individual using ChatGPT as well. I think, again, the key difference here is that we have a proprietary quality indicator. We have full text search across all those content that I showed you from the publishers, extremely valuable. Then we link to what they hold. What have you bought? What have you subscribed to?
Then the ability to buy more. The ability to look at transactions, et cetera. Research Solutions is a relatively small company. We're about 140 people, a micro cap, but we serve some very large customers. That is because these groups need access to literature. They need copyright compliant access to the literature. We are the main company library for many of these big corporations as well as academic institutions for them to get access.
We have the ability to not only expand a lot of these contracts, but to cross-sell different tools and solutions into them. We're doing that. We've done that with Scite, but now we're doing that with the new connectors as well. The market opportunity, again, I highlighted a lot of logos, which is maybe easier than looking at this, is really across the board.
We have lawyers buying articles through us. We have large pharma buying articles through us. We have Hermès, the bag company. I learn new different companies. I'm like, "They buy articles?" That is because R in the R&D really does touch upon everything, and I think it's pretty powerful.
You need access to these. I think in the new world that we're going into, you need access to these in the AI tools, in Claude, in ChatGPT, where people are starting to live, and companies and academics are starting to spend millions of dollars to get there. I'm going to turn this over. I probably went very fast, but again, I blame coffee and trying to get you guys all out the door, to Dave, who's going to talk about what does that mean in terms of financials.
Thanks, Josh. All right. Yeah, Josh went into the specifics on the product side. I thought to complement that, what would be good is to just go through our revenue streams. I won't get into as much details that are on these slides. I encourage everyone to go on the investor website and read through this in detail if you can. I'll keep it fairly high level, though.
We have two revenue streams, two broad revenue streams. One is our transaction business, and that's still 57% of total revenue, so that's the majority of the business. Then we have a platforms business that's 43% of the revenue. They both have unique characteristics that essentially work with each other. I'll get into each product line here in a second.
The platform business is interesting because it has a B2B and a B2C component. What's attractive, the headline here, is over 85% gross margins, and it's closer now to 90% in a recent quarter, and trailing 12 months were above the 87% line.
That gross margin is very healthy, and we've talked a lot today about the fact that bringing on incremental customers really does not add a whole lot of incremental costs, especially with MCPs. We think that's a very important point to highlight here. Very fast-growing. In the last two quarters, we've really had some work on some of our Tier 3 customers that have had retention issues.
We spent a lot of time and resources on managing that, mitigating that, and that should go a long way in the next, we think in the next fiscal year, towards coming back to growth rates that are closer to what we had last fiscal year. I'll get a little bit more into this and the impact of the platform business in a couple slides as well.
Transaction business, just to give a little color, we think of it as document delivery. One of our customers needs to get an article. They come to us to deliver it, and they pay for that article. Typically, the margins there have been around 25%, so much lower than the platform.
You can see on this graph, going back the trailing 12 months, each quarter, there is quite a bit of stability. The one caveat to that is if we have a large customer churn, we had one recently, but even with that, you can see that it's fairly steady. We really think about that business as a low single-digit growth business going forward.
It may take a little bit of time to recover from that large churn, but in the next fiscal year, we should see that growth rate start to tick up when the comparables with that churn fall off. This, I think, is a great slide to show the inflection point from where we were pre-platform growth to where we are now from an adjusted EBITDA and cash flow standpoint.
And you could really see in fiscal 2023, that's when we hit the scalability of the platform. Again, like I'm talking about the platform business being able to bring in additional revenue without additional cost, that's what that's showing here. Trailing 12 months, just to give you a little flavor for where we are now, we're at $6 million in EBITDA and about $5.8 million in cash flow trailing 12 months.
Here, there's a lot of stats here, but I won't go through one by one. The important point is to show that we have a very healthy balance sheet. We have no debt. We have an earn-out that we've been paying to Scite shareholders that's been funded completely out of cash flow from operations.
And we have a very growing. When you look at the blended rate of gross margin, it's now over 50%. So we've been seeing that improve as that mix shift from transactions to platform has occurred. You really have seen the gross margins accelerate to above 50%, and we expect that to continue. Then I think this last slide I have for you really will show where we were to where we've been.
We showed this a few times today in the one-on-one meetings. But you can see in fiscal 2027 to fiscal 2021, we really had a platform percentage of total revenue of 16% that wasn't generating much in the way of EBITDA. The transactions, like I said, it was stable business, very predictable. But we've really accelerated after that inflection point in 2023, and even 2022 where it started.
You can kind of see the EBITDA generation of $6 million, the expanded TAM $15 billion, and these numbers really speak for themselves, and they really show our track record of being able to execute on the platform growth. And we've been able to invest back in the business as well without taking on any debt.
We think, when we do this graph in a couple of years, go through the same exercise, we'll see these numbers continue to accelerate because of the things that Josh talked about, the MCPs and the opportunity that we think AI presents itself for us. When we do this again, we're excited to continue to see these numbers grow in a positive direction. If you have any questions for us, we're happy to answer them. Yes, sir.
Could you talk about the relationships you have with the post-document or library suppliers? Are they exclusive? Or are they non-exclusive? And if not, how do you differentiate yourself from people going to graphs or other means?
I think there's two core relationships. Article Galaxy has relationships with publishers. We are essentially a wholesaler, right? We're selling their articles on their behalf. We're taking a 25% profit margin. We have that with every publisher. You can buy any article you want, even if we don't have an online copy. We have runners that go to libraries and find these very hard and difficult things to get from libraries.
That's one aspect. Those are non-exclusive. We do have competitors where you can buy articles. There's two core competitors there, RightFind, which is a CCC company, and then Dimensions. There's not a whole lot of places that corporations will go to get access to articles. There's really three main ones. We are the only one that can connect into those AI tools. I think there's a differentiator there.
That's one side, and we're effectively buying these articles and reselling them at a higher rate. Scite has also separate relationships with publishers. There's about 40 of those different agreements that I showed. Those we are not buying, we're not paying for. What we are giving them is access to Scite, so their editors can use the tool.
Any other person in the publishing area can use the tool. They can also use those analytics for author marketing, so they can say, "Hey, you published with us. Your paper's been supported." They use that for author marketing. Then one thing which is a benefit to them, but also really a benefit to us, they can integrate our metrics into their product without cost. They put our badges live on those articles.
We're constantly giving to get, and the way that we signed a lot of those deals was to increase their distribution. Our agreements allow us full-text search. What we can show are these snippets, these three-sentence snippets, very much like a Rotten Tomatoes again. What those snippets do is increase views of articles, and with Article Galaxy, it increases document spend.
It increases usage through subscriptions, all those different things. For publishers, we're constantly looking at how, from the Scite side, how can we make sure that they're seeing enough value by giving us that content, that discovery content? Some of that is in flux now, where it's like, "Hey, you guys have these big subscriptions with tools," and people are reading less because of AI. There's this zero-click phenomenon.
What we are working to do with certain publishers is to evolve some of these relationships and be, "Hey, we can be the AI component." You guys are not going to build an MCP, but we've already built it on top of it. Include us. Allow your paywall content to be in that. You have an AI-ready subscription. That's, I think, a little bit of the future to make sure we maintain these relationships and grow these relationships.
That's still pretty early. We haven't yet signed those. We have a lot in our pipeline, and I think that would lead us to also a new revenue stream. If a small publisher said, "We want to sell AI rights to our content to this university," we would be their tech provider through that connector. We already have that connector. We already have their content.
We could be bundled into their subscriptions. We're constantly thinking about it is changing a little bit, but we're always constantly thinking about how can we give stuff to get stuff. We haven't yet paid for any of this content.
Some have asked, and it's like, just doesn't make sense. Here's what we'll give you in exchange for that. Yeah. Any others? If not, we're around, although I'm not around too much, so I'm going to go home. I hope you all enjoy drinks in the mix. Yeah.
Thank you very much.
Appreciate it.