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SSP Innovation Showcase (Spring 2026)
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SSP Innovation Showcase (Spring 2026)
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Language: EN.
Segment:0 .
Welcome, everyone. We're going to give just a minute or two for people to join.
I should say 30s not two minutes. All right. I'm going to kick it off. So Hello and welcome to today's SSP innovation showcase. I am Betsy Donahue, the president and founder of Donahue knows consultancy. Before we get started, I have just a few housekeeping items to review so attendees microphones have been muted automatically.
Please use the Q&A feature on Zoom to enter questions for the moderator and the panelists. You can also use the chat feature to communicate directly with other participants and organizers. The closed captions have been enabled, and to turn on those captions, just select the CC button on the bottom of your Zoom toolbar.
A quick note on SSPS code of conduct for today's meeting. We are committed to diversity, equity, and providing an inclusive meeting environment that fosters open dialogue and the free expression of ideas free of harassment, discrimination, and hostile conduct. We ask all participants, whether speaking or within chat, to consider and debate relevant viewpoints in an orderly, respectful and fair manner.
The society for Scholarly Publishing is committed to complying with competition and antitrust laws. So please avoid any discussion of pricing of market allocation, boycotts, or other topics that could be interpreted as anti-competitive. If any such discussions arise, they shall be stopped immediately to protect both individual participants and the organization today we'll hear from four companies.
Our speakers will go through their presentations one by one, and then we'll take your questions at the end. So when sharing your questions, please indicate which company you are asking about. And before we begin we have a little icebreaker for our speakers here. We're taking kind of a tried and true icebreaker, which was what was your first real job and putting a little spin on it. So the question is, what was your first real job and what's the one thing you learned from that experience that you still use today.
So we'll go in order of the speakers. Jonathan, you're first answering that question. Thanks, Betsy. So my first job was I did yard care. And one of the there was one particular client I did it for. He had a massive property. It was five acres. And I would go and work on Saturdays. I think I was 12 years old.
And I would literally be there for 14 hours. It took me forever to do his yard. And I think the skill, I think the skill that I learned there that I still use is like, you know, there's just a lot of really monotonous work that you need to do that like is maybe not super sexy, fun or glorious, but is actually really rewarding when you finally get it done. And I think that was a good description of what that job was.
So that's great. Jonathan Thanks. Yeah how about you, John. You're next. Oh, my first job is the academic conference coordinator that was in Canada. It was a company. A very small company works as an agent to introduce the Chinese doctors to apply for observership in hospitals in Canada, Canadian hospitals or American hospitals.
So they also we also organize conferences for these people, for all doctors all over the world. But all the conference sizes are very small, so probably like 20 or 30 people. So that's where I started. And what I learned is that I always make a lot of templates to different things. So that's I'm still using that right now. Thanks Thanks, John.
Jennifer, how about you. Looks like we may have lost Jennifer. Oh, Andrew, that means you. I'm sorry. Wait Jennifer's back. Hi, I'm. I would say my first job was bussing tables at a restaurant, and it was for a notorious local restaurant owner.
And she was known for being a real stickler for customer service and making sure that everyone's experience was perfect. And I still definitely use that skill today with all of my customers and clients. Nice awesome. Thanks, Jennifer. Andrew, how about you. I think my first job was in the basement of a hospital.
Moving, shifting, physical x-rays around. You know, like if you take an X-ray at a hospital, you have to keep it for seven years before you can get rid of it or something. And there were a lot of them and they all needed to be moved up continuously. Like as you bring in New things and get rid of old things. And I think what I learned from that job is a little bit like Jonathan kind of just keep going.
If you do a little bit each day, you can tidy up that room eventually. Great, awesome. That's fun. Wonderful now we're going to kick things off. And I am pleased to introduce our first panelist. Jonathan Whelan from Kashmir. Working at the intersection of AI and scholarly content, Jonathan is helping publishers navigate what comes next.
So you're up first, Jonathan. All right. Thanks, Betsy. OK let me. There we go. All right. So, as Betsy mentioned, my name is Jonathan Cohen. I'm the CXO chief experience officer and one of the co-founders of Kashmir.
And as she mentioned, we work with premium content publishers to help them figure out what's next with their content and help them think through their business models and their strategies. And we do that by providing a very flexible tool set that allows them to have control over how that content is used with AI. So we're going to talk a little bit about that here. I wanted to start off with a quick poll.
And I'm just this is just for fun. I just legitimately curious about this from this audience. But the question is, when did you first start heavily using AI as part of your internal workflows. And and so, you know, the just for context, ChatGPT launched in November of 2022. And I know for some of us that feels like it was maybe just yesterday, but it's amazing how fast this is, this field has evolved.
So I'm curious, just feel free to enter this in. This is just for fun. Get a sense of like where everybody is as part of this audience. I'm going to keep moving here. Betsy, how does the poll work. Does it just end, or do we. I'm not sure what the.
I believe it just ends. Yes OK. And we'll see the results when it's done. Yep. OK. I wasn't sure how this works. OK well, so Wiley put out a report end of last year, and their explanation is 2025, where they surveyed their users. Oh, there we go.
OK, cool. So it looks like a good portion of you were in 2025. We've got a couple holdouts who are never going to which I 100% respect and then some pretty early adopters. So very, very helpful. So that the user behaviors though that we're seeing, in 2024, it was 57% of the professionals they surveyed were using AI. And in 2025 it was 84% It was over 50% increase.
And what was interesting is over that same period of time, 53% of the respondents, 53% of the respondents said that I was better than humans and a number of use cases, and by 2025, that had actually dropped to under a third. So what we saw was an increase in adoption, but also an increase in understanding of where the hype for I didn't really match the reality of what people were actually using it for.
So, I started using ChatGPT and in early days, and it very quickly realized that it was very amazing. I couldn't believe that it was real, and it lacked a lot of utility, and a lot of the reason it lacked utility was it just didn't have access to external data, like forgot things really quickly, didn't have access to the internet, had really limited applications, and really quickly realized there that it was only as good as the content that I had to work with.
And so, you know, there are certain domains where having access to trusted content, especially with AI, is critical, because otherwise it's garbage in, garbage out. If you don't have that trusted content. So, you know, say you're a clinical researcher, you know, what are you looking for in an AI tool. Well, you want something that you can use as part of your normal workflow. You want it to have access to trusted resources.
And ideally those resources are as comprehensive as possible. So what are your options here. Well, you can Yolo it. You only live once or just go for it with your preferred agent. So ChatGPT Claude or perplexity. That's where your normal workflows are. But does it have access to trusted resources. Yeah you know, deep research maybe.
Is it comprehensive. Most definitely not. A lot of the content you probably want to access is behind paywalls or subscriptions. Maybe you go for a domain specific solution, like maybe like an open evidence or insight or like a, you know, consensus. And and is that part of your normal workflow. No, but they've gone through and licensed high quality materials.
So it's as trust resources, and it's probably more comprehensive than a lot of the other places you might look. And finally, like maybe you work with a publisher provided tool and trusted resources, definitely. You're already consuming it. Is it comprehensive. No it's going to be constrained to the publisher that you're working with. And it's, you know, and they just can't build platforms that compete with the billions that cloud and GPT have put into their user interfaces.
So what we have here is we have these two entities. We've got users who want access to trusted content in whatever platform they're in, regardless of where they are. And so then the question is, well, what needs to be true in order to unlock this type of experience. And so, you what we found was that publishers needed flexible content infrastructure for how they're able to deploy their content for use with AI.
And so things that this covers is, you know, such as how licenses are, how they are accessed and distributed and how they're controlled, needing tools over how content governance works, about who gets access to what content, where they get access to it, how they get access to it, and then ultimately needing delivery channels to securely and safely deliver that content in a way that it's going to adhere with your data control data control policies, and ultimately being able to track what's happening with your content on an end to end basis.
So, you know, knowing where it's going and what's being done with it so that you can manage reporting back for royalties or potentially for regulatory purposes. So this is what we've built. We've built an infrastructure that's intended to be secure from the ground up. It's air gapped, meaning your content never leaves our system without your permission.
And we've gone through and done, you know, all the primary compliance certificate certifications with soc2, ISO 27001 and GDPR. We built it to be very responsible, and what we mean by that is the publishers are always in control. So they have visibility to their full content lifecycle. You know where it's going. And we have deliberately built this for premium content publishers.
And we recognize that the needs of premium publishers are different than open web publishers. And we very deliberately built it for this particular audience. And then ultimately just built it to be extremely flexible. And will be the first to tell you that we don't know all the answers. And this domain is moving extremely quickly. And so what we've built is an infrastructure that's intended to be very flexible so that as we discover opportunities together of what's working, we can explore a lot.
And then when we find the things that are working, we can scale together. We do this. We've got two core products. One is called cashmere fiber. This is intended to be the content gateway for AI agents. And so basically what that means is instead of having to expose your content to a Google so it gets indexed and you have no idea where it goes, it lives within fiber.
We get and we're able to do the search queries on behalf of the agents while keeping your content secure, and then help them, the agents, to understand where your content is and how to get access to it and how it gets monetized. Our second product is called cashmere connect, and the way you can think about this is it's like a bunch of these composable building blocks that solve different particular problems or challenges within building AI applications.
So and these can be composed together into whatever the use case is that your organization wants to pursue. All right. So who like what are some of these examples of things that people might be looking to build. I've got four use cases here I want to share with you. The first is the integration of cbinsights, Statista, PitchBook and Wiley's content with perplexity.
So perplexity wanted to build access into their platform. They actually just recently launched the product for this. It's called perplexities computer last week, and it gets access to all these premium content data partners. And you know, for the content partners, they had concerns about opening up their corpus of content and letting perplexity get access to it. And so what happens here is Kashmir. We've ingested their content, we've indexed it.
We've gone through and built all the embeddings out and built the integration with perplexity, where we can provide perplexity, secure, and direct access to the content without exposing the full corpus to them. And so this is through our cashmere fiber product. And and so what this is really doing here is it's providing a new top of funnel discovery metric for, for the publishers. And ultimately, when people click on the sources within perplexity, it sends them directly back to the publisher's website, to the deep link of the content itself, where it lives within their platform's second use case is, integrated partner applications.
And so we're building this with Harvard Business Publishing right now, where Harvard had a number of their customers who want to start pulling their content in for use with their training and development programs, which is called their learning experience platform. And so Harvard has a very sophisticated infrastructure that they, you know, migrating it to be useful and integrate with. I was they was going to take them 12 to 18 months to do.
And so they looked for a partner and brought us in. And so we have integrated with their identity provider, with their entitlement system, and given them all the resources and tools that they need to be able to go out and start integrating with some of the AI opportunities that their customers are pulling them into. Use case number three. We're working with a group called blue matrix.
They are a they distribute equity sell side research. So this is for like stock traders and stock analysts. And so they were looking to get their content into perplexity. But because of the industry they work in, there's a lot of regulation. And there's a lot of entitlements that they were very, very sophisticated entitlement solution that they've built. And so they needed to be able to carry those entitlements into the AI application.
And so we have tied into their entitlement platform. We've tied into their identity provider, their authentication, their content distribution. And so now what we're able to do is we've built that connection with them into perplexity. And this product is going to be launching, I think, at the kind of mid April time frame. And what will happen is people will be able to click Connect my equity research and log in with their login with their blue matrix credentials and get access to their entitled content directly within their AI application.
And the last one is Wiley publishing. So we've been working with Wiley for almost a year at this point. And it's just been really cool to see the way that Wiley continues to lean into AI licensing. You know, they're licensing directly to universities and institutions who are wanting to build applications on top of their IP. They're leaning into vertical solutions like veterinarians who are building applications, AI applications specifically for veterinarians.
And they're also starting to sell, you know, be it like B2C and B2B applications, bespoke applications of their content. So, for instance, maybe like a tax accounting firm wants access to Wiley's content. And so Wiley can now sell them a tax application that has access to, you know, a very specific collection of content. So it's really cool to see the ways that they're starting to integrate that.
So just to wrap things up, you know, we've seen that user workflows have shifted. We've all seen this. We know this is happening. AI needs access to trusted content. And really in order to unlock those opportunities. What is needed for publishers is flexible infrastructure that allows them to explore these opportunities. So there's a cashmere from Jonathan.
Thanks for your time. Great Thank you Jonathan. Our next presenter is Jennifer Swafford from vertex communications. Oh why am I seeing John here. All right. So my mistake. Here we go. Sorry, Jennifer didn't going to give you a minor heart attack.
Our next presenter is John Chen with ManTech. John is trying to focus on those hidden risks in research, publishing. John, over to you. OK, it's my turn. So thank you, Betsy, and Thank you, everybody. And my name is John. I'm from a menu check. I'm the director of development of menu check.
Menu check is a very new to in this industry. And it's newly founded this year, but we've been working on this project for two years right now. OK so it's a academic manuscript risk screening system. It's an all in one platform and AI powered. So as you know, as I think we've mentioned about the AI thing, as the Jonathan mentioned about that ChatGPT was launched in 2022 and now we are using AI.
And AI is all over our world. So we can feel that as a publisher in the academic publishing industry, and we feel like that the AI, it's a inevitable that we're facing a situation, that the challenging is increasing and we're not only facing the misconduct from a paper Mills anymore. We're facing the authors.
They're abusing abusively using AI tools in their daily research work. So we're as a publisher, the publisher will take responsibilities and take the reputation of all the contents they published. So as the figure shown on the left side. So the retraction trend is it's drastically increasing after 2022. And as a publisher, this crisis is it's still ongoing because the integrity issues we're having.
And also there's more and more papers with the integrity issues and with potential problems or, or misconduct in the paper will increase the workload and at the same time increase the cost of the workflow of the publisher. And then when there's more things we need to detect and we need to analyze from the title to the references, there is more and more items we need to take a look at, and they will longer the turnaround time.
So the overall time will be very long. So and then when there's issues, when there's issues occurred, when there's misconduct have been reported and it will damage the reputation of both the authors and the publisher. So manual check is providing the solutions. Both in academic integrity screening part and also the manual check quality check.
So first of all the integrity screening we have a comprehensive platform a real time risk databases, then you can just easily use this tool to detect the manuscript. And it would tell you the risk percentage and how good this paper is and how reliability you can trust on this paper. And the manual check quality check is another tour is another part. So we embedded in our tour as well.
It's for the in-house editor to use. And it will save a lot of time for the in-house editor to check the overall structure of this paper. And there's is there any missing content or the consistency of the, of the paper content. So basically it. So as the name stands for, it's a manual check. We check for manuscript.
So what is manual check. It's the AI I powered all in one stop academic manual, manuscript risk screening system. It's a platform, so it provides the underlying architecture that enables the whole editorial team to move from the manual pre-screening to intelligent decision making. So manual check is a tool to give you some ideas to help you to make decisions.
So we have four major parts. We it's covering for more than 40 key indicators. The four major parts. The first part is the manual manual the manuscript structure and the formatting. So it checks the formats, check the title analysis and also the declarations of all the papers. And it also checks if the paper is missing parts and also the author track records.
We track the author, we have the author analysis to see a search on the website. It's automatic operation. So if the author has a history, a retraction history, or some bad behavior in on the internet that it can be alerted. And also we have a content analysis. So this contains a lot of indicators. We have a table integrity which checks the consistency of table citation as well as the citation.
And also we have image check plagiarism and tortured phrases. And also we use the model to compare the model to compare the contents and to tell give you a idea. The percentage of this content well is generated AI generated or not, or human content. And also we have the paper mill detector. So which can tells you that how reliable this paper is.
And also we have a unique part as a reference and a citation analysis. So this will check all the references. It compares the references and the citations in the text in the manual. Check the manuscript text and also it will tells you the relevance of the site of the citation. So if the reference, if the author would cite some references that that's irrelevant to its paper, they will give you alerts.
And also we have this citation check for one author and from one source or from one institution that would avoid citation manipulation. So these are the four major parts. So we have a user case. But we don't have too many users. And we have a user collaborated with the publisher called tech science press. We have 20 more than 20,000 manuscripts handled so far.
And we get the reports is that from all the submissions, we have more than 60% AI alerts. And we have more than 45% generative AI alerts and about around 33% paper mill alerts from all those paper. All those manuscripts are submitted to the system. And by the in-house editors are using this system to check to do their pre-screening and pre peer review checking.
So it would increase more than 10 times of their pre-screening time. So it would be more efficiency for them to handle more people, more papers. And also we have a 30% desk rejection rate and 80% accuracy as predicted rejection. So and also overall it reduces the editorial and peer review costs.
So the technology we use apparently we're using the power task optimization. And also we use the high precision parsing engine. Basically we're using I against AI. So I think the I think at the present time, we're using the magic to fight with the magic. So that's why that's the strategy we're using.
So we're keeping keep developing and keep advancing our technology and to have a more accurate results. And talking about the sovereignty. And we have a first party data. So and the private storage architecture. So you don't have to worry about the sovereignty thing. So we have it's the tourists can be to be and can to can be to see.
So for the enterprise grade security and we have compliant with the GDPR data Protection Regulation. And it's a fully flexible and it's customized. And we have if you it supports the instant the detection protocols. So all privacy is not an issue. So so this is basically the tour and used as AI think it's a efficiency efficient tour to publisher and also to customer to normal scholars as well.
And if you have any questions, you can email me. You can contact me. Thank you. Thank you John, our next presenter for real this time is Jennifer Swafford from vertex communication. Jennifer supports organizations to rethink a tool that everyone uses, but few truly optimize all you. Jennifer Thank you.
Hello, everyone. Thanks for letting us join today. I would say that there's probably at least one person on this call, or somebody on this call teammate that is rushing to get their emails built and out the door. And I can speak from experience on that of two decades or more of building emails for publishers and associations. So I'm here to tell you that we can help you fix that.
So the first thing I'd like to do is I'd like to ask you a quick question. Is your team spending any time or a lot of time building out emails and trying to get them production ready and out the door for your team. So I'll give you a few seconds here. Some of our groups that we work with have a really fine oiled machine.
Others emails and afterthought. Their tool is just sending them for them. Anytime content is published, it sends it out. It's not grouped or curated by an editor. And we know that email is a powerful way to get folks back to your website. There's no obstruction from eye search. It's a direct link, so I'd love to hear what people have to say.
We'll give this a few minutes. A few seconds to bake. Oh, good. OK, interesting. OK, so we have a nice, good broad spectrum for everybody on here. And so we'll go ahead and continue on to the next slide. All right.
So what we typically find when we go into a group and help them get their email out the door, is that one person is copying and pasting all that content by hand. There sometimes missing emails when they don't have a teammate that's helping them there. Sometimes somebody's sick or they leave the organization and there's no SOPs or workflow that somebody can jump right back into and help your team.
So your content is really important. And we know that building that content and research and having it get out to your communities and building those communities and email is a really powerful tool to make that happen. So who are we. We are a vertex communication group. We've actually been working with publishers, scientific publishers and associations for over 20 years.
We are reinvigorating a new ownership and it's very exciting. And because we are decided that it would probably be a good idea to let the world know who we are. We've been very successful by word of mouth. As folks leave an organization and go to the next. But we thought that we'd come here and let you know who we are and what we do. We have 20 years of experience as an organization.
Hundreds of projects, and between us are more than 100 years of experience. So how do we work with our organizations. We manage the process, or we can manage the process for our groups, from soup to nuts start to finish. So content we help them gather it. We gather ads. You know, somebody built a tool that works with email or an email product or an AI tool that connects.
We have probably either are going to use it or have been using it for years, and can help make those systems as organized and clean as possible for you all. We've also helps you as we help manage your email program, get you off the dance floor, having your team, having to build those emails and put them together and let you get back up into the balcony so your team can focus on strategy and how to make your program successful, how to get your content out to your authors and to anybody that needs it.
And then we're managing that process and giving you reporting. Tell you what wins and what worked and what didn't. Second, we are also we have some tools in our tool belt that help us scrape the content, whether it's in staging or already published from your tool, from your publishing tool again, any tool that you are publishing in. And we can put that in an email for you because we can do that.
We can do things such as adding dynamic content, testing subject lines. And then number 3 is an AI powered article selection. And we are actually sending our first friends and family email around this to our team, to an organization that we built this tool for this weekend at a very large conference. So we're really excited about that.
So our publishing tool that we use in action starts from scraping that content. They put the data into a very organized table. We help you build the email. So one of the things we find doesn't happen often enough is we have an email, we have authors who have built this email or I have are in this for the very first time, and we add dynamic content to the email that congratulates them for being an author in that talk or in the AP.
So that's a really powerful way to touch your authors in the email when they're published. We also make sure that it is delivered and on time and goes to the right people. And then we also have in this tool there's some Doi magic I like to call, because you can give us a handful of dois or a lot of them, and we can grab those, put those into our scraper and build out that email with advertisements and editorial comment, whatever you like.
Great so how did we get here. Well, we had a client. We worked with them for many years and they did a manual copy and paste from and built out Excel sheets. It took three to five hours to build an email and sometimes errors unfortunately were caught after the Send.
After we built this or had this tool built, we are able to scrape that content very quickly. We have ads and editorial notes already prepped and ready into the templates, so as soon as the content is embargoed, we can send it out to folks during conferences. And we can have that all prepped right before conference starts, so that while conferences are happening, it has to it can go out to them and they don't have to worry about it in the middle of a very large conference.
What's coming soon. And we're doing a friends and family. This weekend is AI powered article selection and personalization. I did hear from that first pole that some of you are not interested in that, but for those who are, it is a you're in full control. You get to pick and choose how much I you want to use, how much traditional content you want to use.
You can go across journals, you can go deep into the different categories or topics that are available as well. So I'd like to end this with one quick poll and ask you, you know, is this something that you all need. So will take a few seconds to rate your current situation.
Are you sending out that email. You've got it completely handled is number one. Number 10 is come. Please help us. Give that a second to bake. Well, while we're doing that, it was very grateful for you all to let us join you today.
It's also been really. I will be stealing John's magic on magic. That was a really great. All right. Thank you so much. For those of you who are interested or would like to speak with us, my name again, is Jennifer Swafford. My email address is Jay Swafford at vertex communications.com. We'd love to hear from you.
Great Thanks very much, Jennifer. Our next and final presenter is Andrew Preston. So via Cassini, Andrew is exploring new ways to reconnect research with the people it's meant to reach. Over to you, Andrew. Thank you. Betsy I don't know that I wrote that sentence. Sentence is really good. I'm going to be using that.
It's free. It's yours. I wrote it last night at like 1130. Thank you. Yeah let's see. So so I'm a researcher. I'm a physicist originally. And I think just about any researcher you'll talk about, talk to the reason they've historically or historically published in the journals that I published in was all down to the community.
You know, my collaborators were publishing those journals. Certainly my supervisors were. We knew that editors, your competitors are there all these sorts of things. There was a real sense of community around the journal, that's kind of, you know, over the last little while, evolved a lot with, you know, discovery tools like Google Scholar, et cetera you go to the journal lists now, even on this call today, you know, in the first two presentations, there's so much talk about AI and what it's doing.
And a lot of it is kind of drawing people away from the journal, whether it's on the consumption end, like we kind of heard with Kashmir or on the editorial side with manutuke. And I guess kind of the way we see it is that these changes are significantly impacting the relevance of journals going forward, and that is having an impact on the ability for, any given journal to attract the right authors, reviewers and editors to come along and contribute.
And so I guess our contention is that, counterintuitively, as AI gets more and more important and valuable, actually probably the most important thing to be thinking about is the humans behind the AI. And so you can think of as Cassini, think of Cassini as a way of trying to get back in touch with the humans behind, behind the AI. And what we've done is built a seminar platform, but a really good way of connecting with researchers and building a community around the research as you're connecting with.
So our seminar platform integrates with journals or a portfolio of journals to draw in a community of engaged authors, reviewers, and editors from around the world. We're then able to track and measure the impact of this engagement, showing how it drives submissions, submission citations, all these sorts of things kind of out of the box. And the way we built the platform with AI, et cetera does make it easy to do this in a hands off way.
Oh, there we go. The slides are back. So it's kind of the let's say problem solution statement. What is the product look like. So we're all in a Zoom webinar right now. Here's the Cassini version of a meeting. We're actually here wrapping around Zoom. And you've got your standard Zoom experience in the middle there.
But in this case, this is a seminar about acoustic and electric waves. In metamaterials. You can see the Zoom meeting, but down below you can also see the community of people who are in this meeting and involved. So, you know, you're in a webinar situation right now, you might not know who else is in the room. Even if it's a Zoom meeting, you might just have a list of names on the side.
But actually really important in this research context is knowing who's there with you, who's interested in this topic, why are they interested in this topic. And so we've put a lot of effort into, in this live kind of event situation, to make it possible to know exactly who's in the room with you and for you to kind of get to know them and, and ultimately connect with them.
And so this is a screenshot of the live event. But obviously behind the scenes we're doing a lot. So we have tools that will help you. Also defined as an organizer, the people that should be in this live event that might not know about it yet. So audience building these sorts of things as well. And it doesn't just end with the live event. You know, as a younger generation, the YouTube, TikTok generation of, of researchers kind of emerges.
There's a growing preprints for viewing. And so the idea is that for any given PDF, any given paper in a journal, you can get in the authors to give a talk, and there may or may not be a live event, but you also end up with a recording, something that an engaging video that people can come in and watch after the fact. And so you can think of this also as augmenting the PDF with video.
And it's not just the video. We do a lot to look inside what the speaker has spoken about, extract all of the slides, make them searchable, make them queryable by AI so you can ask any seminar question and of course any reference in the videos as well as extracted and connected to the literature. So it's very connected. And that connection to the literature is important. So I'm showing here an article page, the same article page for this PDF.
And you can see how we've been able to actually embed the seminar into the journal page. And we can do that kind of through an automatic one click Configuration for upcoming seminars. There's an option there to RSVP for seminars that have been held already. You can watch the recording, but we go beyond that in terms of integrating. So we will, you know, connect into tools like dimensions for discovery and EndNote for our reference management and all these tools, these videos, these seminars will appear and be discoverable.
So we're fully integrated into the scholarly ecosystem. Make building something really, really useful for researchers. So that's the product. What's the outcome we're showing you here Cassini pulse where members of that community, you know, they've engaged in the platform in various ways. And we can show how engaged they are. And so you can start to get an idea of who in your community is most engaged, might be interested in publishing, becoming a guest editor, these sorts of things.
And so kind of out of the box, as I said, these sorts of tools start to emerge. We kind wrap all this up, all these things that are happening. It's something we call the Cassini effect and what that is, is basically, as you build these communities on Cassini, we can show and measure for any journal that it will lead to an increase in high quality submissions and increase in citations relative to baseline downloads, and then also things like guest editors.
So if you're running special collections, it actually turns out to be a great way to find guest editors for those special collections and these sorts of things. So giving you here an example, a case study of a journal that started out as a Q2 title, publishing about 200 articles per year grew significantly over the months they built a community of, you know, eight, 800, maybe 1,000 people on Cassini is now Q1 growing rapidly really strong journal.
And so it's been great to see the global community that's been built around us and the engagement that's resulted. And I guess I'll just leave you with a vision or the idea here. AI is becoming more important, but the humans behind it are critical too. How can we build that community, build the human layer and integrate it back into the journal? So we're showing you here a journal that uses Cassini. We've shown you here on the left, the community.
And, you know, this should really be the thing that is what you come to the journal to discover. So I will end there. Great Thank you, Andrew. And now we've got about two minutes or so for questions. We've had a couple come in while folks were speaking. I'm going to start with this one here. So this one goes to Jonathan and Kashmir.
How do you balance broad distribution with protecting subscription and licensing models. Good question. I think ultimately, it's up to the publisher and their strategy and how they want to pursue it. So some publishers are looking for help in getting exposure to their content and being able to make sure that, like, they're exploring like that's even like just a new potential revenue channel.
So like there's some that are looking for that. And then there's others that are looking for more, you know, kind of access based controls. And so really we like I said, like we really see ourselves as like an ally for the publishers. And it's like we've got solutions and things that we're learning in the market, and we'll bring those as best we can and share those with you. And if you have opportunities that you've identified or that you want to explore, we can help you do that as well.
Nice then I've got a selfish one myself. I'd love to hear the story of the name Kashmir. Well, that's a funny story. We originally so my partners and I are huge fans of the T.V show Seinfeld. And we actually wanted to name the company. So George and Jerry and Kramer all have like their pseudo companies.
And we wanted, we wanted to call the company Vandelay. Like, I write Vandelay industries, but we didn't think that would go over very well. And so we my partner monk, had idea the idea of Kashmir for one of his previous businesses. And so we ended up we really liked that and kind of pulled it in and, and it feels really it feels like a good fit. Pun intended. Nice to the touch, as they say.
Yeah Thanks. Awesome related to that, same with Cassini. Andrew, where did that. Yeah where'd that. Where did that come from. What's the origin story there. It's Yeah. My co-founders, Ben and John. It comes out of their, I guess, startup name generator.
You know, we're all involved in a number of startups, but the idea is pick a famous scientist and change their name slightly until you can get the dotcom. So in this case, Giovanni Cassini was a famous astronomer. Discovered the rings around Saturn. Cassini was also a probe that went out to Saturn a few years ago. And so we changed his name slightly and got the.the.com. And actually, just one kind of nice related piece of information tied to that is Cassini was actually doing his work analyzing the rings of Saturn during a pandemic back in the 17th century or so.
And so we got started, during the pandemic. So that's very cool. Thank you. That was just coming from my curiosity there. We do have an attendee question for John. It's a question with a couple questions inside of it. Very meta. What is the manuscript format. That is, can you check both word files and PDF files that are submitted.
It's the first question. And then number two, are you checking against third party databases for example PubMed PubMed central, crossref, orcid et cetera. So it supports multi formats. It supports the word formats and also the PDFs. And you can just drag, drag and drop the your file in the system.
And it will automatically around the detection. So for the second question is that. I've, I don't know what this question means by the PubMed central because we have do you mean that do we compare the data with the central or where we compare with. The images or what? Could you be more specific.
We can wait to see who whoever answered that can provide some specificity. So probably let's park that one John and come back to it once that person replies. Oh wait, I'm thinking about citation analysis. Oh citation analysis. Basically, we're only checking the database, the citations from sources like from journals and the major affiliations and the corresponding affiliations and the corresponding authors and the first authors.
So we're matching all the authors if there's within one manuscript and if there are multiple, there are citation from one group of authors or from one author. They will give you alerts and if there's some many references are from one institution, they will give you alerts. And if there's a over citations from one journal and give you an alert to so.
And also we checked the relevance and to compare is basically the technology that we used to compare the keywords thing. So we don't compare with the completely with the third party databases. Also we, we, we compare with the crossref. So OK great. Thank you. And then my add on question for you is John, you had mentioned this is a project that's been in the works for a couple years.
Right and your editorial team at the current publisher where you reside, have been using this for a while. Are there plans to make this available outside of that publisher? Yes, that's why we're first of all, we I'm from a publisher and it's called Texas Tech science press. And firstly, we have a lot of challenges because there's a paper Mills are always targeting on the publishers with the small size, with a couple of other journals and easy to be infiltrate.
So so we, we feel like we may need a lot of workflows to fix the, a lot of loopholes on our, you know, the daily work. So and the paper Mills, we use a lot of strategies to testing your weakness. Like say if you are lack of checking at the final proof stage, they will change the data on the proof when they return the revision and they will change slightly, maybe one author or two.
And if you're lacking the pre-screening process and they will using the bulk submissions to take up all your time to take up all your human resources, and you don't have enough time for those good papers. So that's why we have an idea to invest the tool that we're using AI to shorten the time and to save and have a more accurate results to help us to make a decision.
So that's why that's how we started. And then right now we thought that this is a good tool. And then it could be a very product, a very good product. We can provide it to all other publishers or authors say whoever needs it. Thank you John. And then Jennifer, we've got one here for you. As expectations rise for more segmentation and more personalization with email.
How does vertex help publishing and society staff in particular, stay focused on their mission driven strategy, rather than that day to day execution. Well, our team is definitely very experienced in dealing with looking at the segmentation of audiences around the publications. And we're also looking at we're using the AI model for content. But we're also looking at as a data selection opportunity as well.
You know, we always know when people are clicking, we can follow those clicks onto your journal pages to see what other places they're going. That allows us to build out triggered messages. So we're not just sending these big bulk blasts to folks anymore. We're actually using their triggers and intelligence of what they're interested in, what they're reading and we're using that to build the segments out.
We also have keywords, topics, any of that can be sliced and diced based on the content that they are viewing from the emails themselves. Nice Thank you. Then I've got one from my own personal experience. This might be a little telling. So barriers to change, right? So your solutions are bringing a big change within organizations. And I know from firsthand experience that people like to hold on to the way they do things right.
So this human element element, to kind of pull that manual way out of people's hands, could you talk a little bit about how you help support your clients in that change. Absolutely I always like to say that I live in the tide change. So if the ocean is changing tide, I'm in it. And that's what we do with groups. But we're not into to disrupt too much. We come in, we assess what folks are doing.
We choose the wins or the things that are small, low hanging fruit that we can grab. And then we show those successes and then step into it easily. We don't need to do a whole seed change to make an email program really successful. But the baby steps can be really powerful and we make it easy. You know, it's not a matter of know, we were talking to humans. We're we're every each one of our clients has reps that help them really transform their program.
And so it's a little bit softer than coming in and saying, hey, we're going to rip this program out of your hands and make it a different way. Yeah, I mean, I hinted on LinkedIn there might be a puppy destroying my office, but luckily my kid was awake from her spring break, so she's puppy sitting but raising a puppy right now. I've learned that. I'm reminded of that when they're holding on to something trying to directly take it away is not the way right?
You got to come at it with a different approach. Well, it looks like we're right on time. So that's been the hour. A big Thanks to all of our panelists, and Thank you all for joining today as attendees. And as a related note, SSP does ask for a quick favor. We want your feedback. So please do consider taking just a few minutes to complete a session evaluation form.
It's invaluable to us. It's SSP and as a reminder, a recording of today's session will also be posted on the SSP on demand library in a few days. So Yeah, this concludes today's SSP innovation showcase. Thanks again, and have a great day everyone. Thank you. Bye Thank you. Thank you. Take care.
Segment:0 .
Welcome, everyone. We're going to give just a minute or two for people to join.
I should say 30s not two minutes. All right. I'm going to kick it off. So Hello and welcome to today's SSP innovation showcase. I am Betsy Donahue, the president and founder of Donahue knows consultancy. Before we get started, I have just a few housekeeping items to review so attendees microphones have been muted automatically.
Please use the Q&A feature on Zoom to enter questions for the moderator and the panelists. You can also use the chat feature to communicate directly with other participants and organizers. The closed captions have been enabled, and to turn on those captions, just select the CC button on the bottom of your Zoom toolbar.
A quick note on SSPS code of conduct for today's meeting. We are committed to diversity, equity, and providing an inclusive meeting environment that fosters open dialogue and the free expression of ideas free of harassment, discrimination, and hostile conduct. We ask all participants, whether speaking or within chat, to consider and debate relevant viewpoints in an orderly, respectful and fair manner.
The society for Scholarly Publishing is committed to complying with competition and antitrust laws. So please avoid any discussion of pricing of market allocation, boycotts, or other topics that could be interpreted as anti-competitive. If any such discussions arise, they shall be stopped immediately to protect both individual participants and the organization today we'll hear from four companies.
Our speakers will go through their presentations one by one, and then we'll take your questions at the end. So when sharing your questions, please indicate which company you are asking about. And before we begin we have a little icebreaker for our speakers here. We're taking kind of a tried and true icebreaker, which was what was your first real job and putting a little spin on it. So the question is, what was your first real job and what's the one thing you learned from that experience that you still use today.
So we'll go in order of the speakers. Jonathan, you're first answering that question. Thanks, Betsy. So my first job was I did yard care. And one of the there was one particular client I did it for. He had a massive property. It was five acres. And I would go and work on Saturdays. I think I was 12 years old.
And I would literally be there for 14 hours. It took me forever to do his yard. And I think the skill, I think the skill that I learned there that I still use is like, you know, there's just a lot of really monotonous work that you need to do that like is maybe not super sexy, fun or glorious, but is actually really rewarding when you finally get it done. And I think that was a good description of what that job was.
So that's great. Jonathan Thanks. Yeah how about you, John. You're next. Oh, my first job is the academic conference coordinator that was in Canada. It was a company. A very small company works as an agent to introduce the Chinese doctors to apply for observership in hospitals in Canada, Canadian hospitals or American hospitals.
So they also we also organize conferences for these people, for all doctors all over the world. But all the conference sizes are very small, so probably like 20 or 30 people. So that's where I started. And what I learned is that I always make a lot of templates to different things. So that's I'm still using that right now. Thanks Thanks, John.
Jennifer, how about you. Looks like we may have lost Jennifer. Oh, Andrew, that means you. I'm sorry. Wait Jennifer's back. Hi, I'm. I would say my first job was bussing tables at a restaurant, and it was for a notorious local restaurant owner.
And she was known for being a real stickler for customer service and making sure that everyone's experience was perfect. And I still definitely use that skill today with all of my customers and clients. Nice awesome. Thanks, Jennifer. Andrew, how about you. I think my first job was in the basement of a hospital.
Moving, shifting, physical x-rays around. You know, like if you take an X-ray at a hospital, you have to keep it for seven years before you can get rid of it or something. And there were a lot of them and they all needed to be moved up continuously. Like as you bring in New things and get rid of old things. And I think what I learned from that job is a little bit like Jonathan kind of just keep going.
If you do a little bit each day, you can tidy up that room eventually. Great, awesome. That's fun. Wonderful now we're going to kick things off. And I am pleased to introduce our first panelist. Jonathan Whelan from Kashmir. Working at the intersection of AI and scholarly content, Jonathan is helping publishers navigate what comes next.
So you're up first, Jonathan. All right. Thanks, Betsy. OK let me. There we go. All right. So, as Betsy mentioned, my name is Jonathan Cohen. I'm the CXO chief experience officer and one of the co-founders of Kashmir.
And as she mentioned, we work with premium content publishers to help them figure out what's next with their content and help them think through their business models and their strategies. And we do that by providing a very flexible tool set that allows them to have control over how that content is used with AI. So we're going to talk a little bit about that here. I wanted to start off with a quick poll.
And I'm just this is just for fun. I just legitimately curious about this from this audience. But the question is, when did you first start heavily using AI as part of your internal workflows. And and so, you know, the just for context, ChatGPT launched in November of 2022. And I know for some of us that feels like it was maybe just yesterday, but it's amazing how fast this is, this field has evolved.
So I'm curious, just feel free to enter this in. This is just for fun. Get a sense of like where everybody is as part of this audience. I'm going to keep moving here. Betsy, how does the poll work. Does it just end, or do we. I'm not sure what the.
I believe it just ends. Yes OK. And we'll see the results when it's done. Yep. OK. I wasn't sure how this works. OK well, so Wiley put out a report end of last year, and their explanation is 2025, where they surveyed their users. Oh, there we go.
OK, cool. So it looks like a good portion of you were in 2025. We've got a couple holdouts who are never going to which I 100% respect and then some pretty early adopters. So very, very helpful. So that the user behaviors though that we're seeing, in 2024, it was 57% of the professionals they surveyed were using AI. And in 2025 it was 84% It was over 50% increase.
And what was interesting is over that same period of time, 53% of the respondents, 53% of the respondents said that I was better than humans and a number of use cases, and by 2025, that had actually dropped to under a third. So what we saw was an increase in adoption, but also an increase in understanding of where the hype for I didn't really match the reality of what people were actually using it for.
So, I started using ChatGPT and in early days, and it very quickly realized that it was very amazing. I couldn't believe that it was real, and it lacked a lot of utility, and a lot of the reason it lacked utility was it just didn't have access to external data, like forgot things really quickly, didn't have access to the internet, had really limited applications, and really quickly realized there that it was only as good as the content that I had to work with.
And so, you know, there are certain domains where having access to trusted content, especially with AI, is critical, because otherwise it's garbage in, garbage out. If you don't have that trusted content. So, you know, say you're a clinical researcher, you know, what are you looking for in an AI tool. Well, you want something that you can use as part of your normal workflow. You want it to have access to trusted resources.
And ideally those resources are as comprehensive as possible. So what are your options here. Well, you can Yolo it. You only live once or just go for it with your preferred agent. So ChatGPT Claude or perplexity. That's where your normal workflows are. But does it have access to trusted resources. Yeah you know, deep research maybe.
Is it comprehensive. Most definitely not. A lot of the content you probably want to access is behind paywalls or subscriptions. Maybe you go for a domain specific solution, like maybe like an open evidence or insight or like a, you know, consensus. And and is that part of your normal workflow. No, but they've gone through and licensed high quality materials.
So it's as trust resources, and it's probably more comprehensive than a lot of the other places you might look. And finally, like maybe you work with a publisher provided tool and trusted resources, definitely. You're already consuming it. Is it comprehensive. No it's going to be constrained to the publisher that you're working with. And it's, you know, and they just can't build platforms that compete with the billions that cloud and GPT have put into their user interfaces.
So what we have here is we have these two entities. We've got users who want access to trusted content in whatever platform they're in, regardless of where they are. And so then the question is, well, what needs to be true in order to unlock this type of experience. And so, you what we found was that publishers needed flexible content infrastructure for how they're able to deploy their content for use with AI.
And so things that this covers is, you know, such as how licenses are, how they are accessed and distributed and how they're controlled, needing tools over how content governance works, about who gets access to what content, where they get access to it, how they get access to it, and then ultimately needing delivery channels to securely and safely deliver that content in a way that it's going to adhere with your data control data control policies, and ultimately being able to track what's happening with your content on an end to end basis.
So, you know, knowing where it's going and what's being done with it so that you can manage reporting back for royalties or potentially for regulatory purposes. So this is what we've built. We've built an infrastructure that's intended to be secure from the ground up. It's air gapped, meaning your content never leaves our system without your permission.
And we've gone through and done, you know, all the primary compliance certificate certifications with soc2, ISO 27001 and GDPR. We built it to be very responsible, and what we mean by that is the publishers are always in control. So they have visibility to their full content lifecycle. You know where it's going. And we have deliberately built this for premium content publishers.
And we recognize that the needs of premium publishers are different than open web publishers. And we very deliberately built it for this particular audience. And then ultimately just built it to be extremely flexible. And will be the first to tell you that we don't know all the answers. And this domain is moving extremely quickly. And so what we've built is an infrastructure that's intended to be very flexible so that as we discover opportunities together of what's working, we can explore a lot.
And then when we find the things that are working, we can scale together. We do this. We've got two core products. One is called cashmere fiber. This is intended to be the content gateway for AI agents. And so basically what that means is instead of having to expose your content to a Google so it gets indexed and you have no idea where it goes, it lives within fiber.
We get and we're able to do the search queries on behalf of the agents while keeping your content secure, and then help them, the agents, to understand where your content is and how to get access to it and how it gets monetized. Our second product is called cashmere connect, and the way you can think about this is it's like a bunch of these composable building blocks that solve different particular problems or challenges within building AI applications.
So and these can be composed together into whatever the use case is that your organization wants to pursue. All right. So who like what are some of these examples of things that people might be looking to build. I've got four use cases here I want to share with you. The first is the integration of cbinsights, Statista, PitchBook and Wiley's content with perplexity.
So perplexity wanted to build access into their platform. They actually just recently launched the product for this. It's called perplexities computer last week, and it gets access to all these premium content data partners. And you know, for the content partners, they had concerns about opening up their corpus of content and letting perplexity get access to it. And so what happens here is Kashmir. We've ingested their content, we've indexed it.
We've gone through and built all the embeddings out and built the integration with perplexity, where we can provide perplexity, secure, and direct access to the content without exposing the full corpus to them. And so this is through our cashmere fiber product. And and so what this is really doing here is it's providing a new top of funnel discovery metric for, for the publishers. And ultimately, when people click on the sources within perplexity, it sends them directly back to the publisher's website, to the deep link of the content itself, where it lives within their platform's second use case is, integrated partner applications.
And so we're building this with Harvard Business Publishing right now, where Harvard had a number of their customers who want to start pulling their content in for use with their training and development programs, which is called their learning experience platform. And so Harvard has a very sophisticated infrastructure that they, you know, migrating it to be useful and integrate with. I was they was going to take them 12 to 18 months to do.
And so they looked for a partner and brought us in. And so we have integrated with their identity provider, with their entitlement system, and given them all the resources and tools that they need to be able to go out and start integrating with some of the AI opportunities that their customers are pulling them into. Use case number three. We're working with a group called blue matrix.
They are a they distribute equity sell side research. So this is for like stock traders and stock analysts. And so they were looking to get their content into perplexity. But because of the industry they work in, there's a lot of regulation. And there's a lot of entitlements that they were very, very sophisticated entitlement solution that they've built. And so they needed to be able to carry those entitlements into the AI application.
And so we have tied into their entitlement platform. We've tied into their identity provider, their authentication, their content distribution. And so now what we're able to do is we've built that connection with them into perplexity. And this product is going to be launching, I think, at the kind of mid April time frame. And what will happen is people will be able to click Connect my equity research and log in with their login with their blue matrix credentials and get access to their entitled content directly within their AI application.
And the last one is Wiley publishing. So we've been working with Wiley for almost a year at this point. And it's just been really cool to see the way that Wiley continues to lean into AI licensing. You know, they're licensing directly to universities and institutions who are wanting to build applications on top of their IP. They're leaning into vertical solutions like veterinarians who are building applications, AI applications specifically for veterinarians.
And they're also starting to sell, you know, be it like B2C and B2B applications, bespoke applications of their content. So, for instance, maybe like a tax accounting firm wants access to Wiley's content. And so Wiley can now sell them a tax application that has access to, you know, a very specific collection of content. So it's really cool to see the ways that they're starting to integrate that.
So just to wrap things up, you know, we've seen that user workflows have shifted. We've all seen this. We know this is happening. AI needs access to trusted content. And really in order to unlock those opportunities. What is needed for publishers is flexible infrastructure that allows them to explore these opportunities. So there's a cashmere from Jonathan.
Thanks for your time. Great Thank you Jonathan. Our next presenter is Jennifer Swafford from vertex communications. Oh why am I seeing John here. All right. So my mistake. Here we go. Sorry, Jennifer didn't going to give you a minor heart attack.
Our next presenter is John Chen with ManTech. John is trying to focus on those hidden risks in research, publishing. John, over to you. OK, it's my turn. So thank you, Betsy, and Thank you, everybody. And my name is John. I'm from a menu check. I'm the director of development of menu check.
Menu check is a very new to in this industry. And it's newly founded this year, but we've been working on this project for two years right now. OK so it's a academic manuscript risk screening system. It's an all in one platform and AI powered. So as you know, as I think we've mentioned about the AI thing, as the Jonathan mentioned about that ChatGPT was launched in 2022 and now we are using AI.
And AI is all over our world. So we can feel that as a publisher in the academic publishing industry, and we feel like that the AI, it's a inevitable that we're facing a situation, that the challenging is increasing and we're not only facing the misconduct from a paper Mills anymore. We're facing the authors.
They're abusing abusively using AI tools in their daily research work. So we're as a publisher, the publisher will take responsibilities and take the reputation of all the contents they published. So as the figure shown on the left side. So the retraction trend is it's drastically increasing after 2022. And as a publisher, this crisis is it's still ongoing because the integrity issues we're having.
And also there's more and more papers with the integrity issues and with potential problems or, or misconduct in the paper will increase the workload and at the same time increase the cost of the workflow of the publisher. And then when there's more things we need to detect and we need to analyze from the title to the references, there is more and more items we need to take a look at, and they will longer the turnaround time.
So the overall time will be very long. So and then when there's issues, when there's issues occurred, when there's misconduct have been reported and it will damage the reputation of both the authors and the publisher. So manual check is providing the solutions. Both in academic integrity screening part and also the manual check quality check.
So first of all the integrity screening we have a comprehensive platform a real time risk databases, then you can just easily use this tool to detect the manuscript. And it would tell you the risk percentage and how good this paper is and how reliability you can trust on this paper. And the manual check quality check is another tour is another part. So we embedded in our tour as well.
It's for the in-house editor to use. And it will save a lot of time for the in-house editor to check the overall structure of this paper. And there's is there any missing content or the consistency of the, of the paper content. So basically it. So as the name stands for, it's a manual check. We check for manuscript.
So what is manual check. It's the AI I powered all in one stop academic manual, manuscript risk screening system. It's a platform, so it provides the underlying architecture that enables the whole editorial team to move from the manual pre-screening to intelligent decision making. So manual check is a tool to give you some ideas to help you to make decisions.
So we have four major parts. We it's covering for more than 40 key indicators. The four major parts. The first part is the manual manual the manuscript structure and the formatting. So it checks the formats, check the title analysis and also the declarations of all the papers. And it also checks if the paper is missing parts and also the author track records.
We track the author, we have the author analysis to see a search on the website. It's automatic operation. So if the author has a history, a retraction history, or some bad behavior in on the internet that it can be alerted. And also we have a content analysis. So this contains a lot of indicators. We have a table integrity which checks the consistency of table citation as well as the citation.
And also we have image check plagiarism and tortured phrases. And also we use the model to compare the model to compare the contents and to tell give you a idea. The percentage of this content well is generated AI generated or not, or human content. And also we have the paper mill detector. So which can tells you that how reliable this paper is.
And also we have a unique part as a reference and a citation analysis. So this will check all the references. It compares the references and the citations in the text in the manual. Check the manuscript text and also it will tells you the relevance of the site of the citation. So if the reference, if the author would cite some references that that's irrelevant to its paper, they will give you alerts.
And also we have this citation check for one author and from one source or from one institution that would avoid citation manipulation. So these are the four major parts. So we have a user case. But we don't have too many users. And we have a user collaborated with the publisher called tech science press. We have 20 more than 20,000 manuscripts handled so far.
And we get the reports is that from all the submissions, we have more than 60% AI alerts. And we have more than 45% generative AI alerts and about around 33% paper mill alerts from all those paper. All those manuscripts are submitted to the system. And by the in-house editors are using this system to check to do their pre-screening and pre peer review checking.
So it would increase more than 10 times of their pre-screening time. So it would be more efficiency for them to handle more people, more papers. And also we have a 30% desk rejection rate and 80% accuracy as predicted rejection. So and also overall it reduces the editorial and peer review costs.
So the technology we use apparently we're using the power task optimization. And also we use the high precision parsing engine. Basically we're using I against AI. So I think the I think at the present time, we're using the magic to fight with the magic. So that's why that's the strategy we're using.
So we're keeping keep developing and keep advancing our technology and to have a more accurate results. And talking about the sovereignty. And we have a first party data. So and the private storage architecture. So you don't have to worry about the sovereignty thing. So we have it's the tourists can be to be and can to can be to see.
So for the enterprise grade security and we have compliant with the GDPR data Protection Regulation. And it's a fully flexible and it's customized. And we have if you it supports the instant the detection protocols. So all privacy is not an issue. So so this is basically the tour and used as AI think it's a efficiency efficient tour to publisher and also to customer to normal scholars as well.
And if you have any questions, you can email me. You can contact me. Thank you. Thank you John, our next presenter for real this time is Jennifer Swafford from vertex communication. Jennifer supports organizations to rethink a tool that everyone uses, but few truly optimize all you. Jennifer Thank you.
Hello, everyone. Thanks for letting us join today. I would say that there's probably at least one person on this call, or somebody on this call teammate that is rushing to get their emails built and out the door. And I can speak from experience on that of two decades or more of building emails for publishers and associations. So I'm here to tell you that we can help you fix that.
So the first thing I'd like to do is I'd like to ask you a quick question. Is your team spending any time or a lot of time building out emails and trying to get them production ready and out the door for your team. So I'll give you a few seconds here. Some of our groups that we work with have a really fine oiled machine.
Others emails and afterthought. Their tool is just sending them for them. Anytime content is published, it sends it out. It's not grouped or curated by an editor. And we know that email is a powerful way to get folks back to your website. There's no obstruction from eye search. It's a direct link, so I'd love to hear what people have to say.
We'll give this a few minutes. A few seconds to bake. Oh, good. OK, interesting. OK, so we have a nice, good broad spectrum for everybody on here. And so we'll go ahead and continue on to the next slide. All right.
So what we typically find when we go into a group and help them get their email out the door, is that one person is copying and pasting all that content by hand. There sometimes missing emails when they don't have a teammate that's helping them there. Sometimes somebody's sick or they leave the organization and there's no SOPs or workflow that somebody can jump right back into and help your team.
So your content is really important. And we know that building that content and research and having it get out to your communities and building those communities and email is a really powerful tool to make that happen. So who are we. We are a vertex communication group. We've actually been working with publishers, scientific publishers and associations for over 20 years.
We are reinvigorating a new ownership and it's very exciting. And because we are decided that it would probably be a good idea to let the world know who we are. We've been very successful by word of mouth. As folks leave an organization and go to the next. But we thought that we'd come here and let you know who we are and what we do. We have 20 years of experience as an organization.
Hundreds of projects, and between us are more than 100 years of experience. So how do we work with our organizations. We manage the process, or we can manage the process for our groups, from soup to nuts start to finish. So content we help them gather it. We gather ads. You know, somebody built a tool that works with email or an email product or an AI tool that connects.
We have probably either are going to use it or have been using it for years, and can help make those systems as organized and clean as possible for you all. We've also helps you as we help manage your email program, get you off the dance floor, having your team, having to build those emails and put them together and let you get back up into the balcony so your team can focus on strategy and how to make your program successful, how to get your content out to your authors and to anybody that needs it.
And then we're managing that process and giving you reporting. Tell you what wins and what worked and what didn't. Second, we are also we have some tools in our tool belt that help us scrape the content, whether it's in staging or already published from your tool, from your publishing tool again, any tool that you are publishing in. And we can put that in an email for you because we can do that.
We can do things such as adding dynamic content, testing subject lines. And then number 3 is an AI powered article selection. And we are actually sending our first friends and family email around this to our team, to an organization that we built this tool for this weekend at a very large conference. So we're really excited about that.
So our publishing tool that we use in action starts from scraping that content. They put the data into a very organized table. We help you build the email. So one of the things we find doesn't happen often enough is we have an email, we have authors who have built this email or I have are in this for the very first time, and we add dynamic content to the email that congratulates them for being an author in that talk or in the AP.
So that's a really powerful way to touch your authors in the email when they're published. We also make sure that it is delivered and on time and goes to the right people. And then we also have in this tool there's some Doi magic I like to call, because you can give us a handful of dois or a lot of them, and we can grab those, put those into our scraper and build out that email with advertisements and editorial comment, whatever you like.
Great so how did we get here. Well, we had a client. We worked with them for many years and they did a manual copy and paste from and built out Excel sheets. It took three to five hours to build an email and sometimes errors unfortunately were caught after the Send.
After we built this or had this tool built, we are able to scrape that content very quickly. We have ads and editorial notes already prepped and ready into the templates, so as soon as the content is embargoed, we can send it out to folks during conferences. And we can have that all prepped right before conference starts, so that while conferences are happening, it has to it can go out to them and they don't have to worry about it in the middle of a very large conference.
What's coming soon. And we're doing a friends and family. This weekend is AI powered article selection and personalization. I did hear from that first pole that some of you are not interested in that, but for those who are, it is a you're in full control. You get to pick and choose how much I you want to use, how much traditional content you want to use.
You can go across journals, you can go deep into the different categories or topics that are available as well. So I'd like to end this with one quick poll and ask you, you know, is this something that you all need. So will take a few seconds to rate your current situation.
Are you sending out that email. You've got it completely handled is number one. Number 10 is come. Please help us. Give that a second to bake. Well, while we're doing that, it was very grateful for you all to let us join you today.
It's also been really. I will be stealing John's magic on magic. That was a really great. All right. Thank you so much. For those of you who are interested or would like to speak with us, my name again, is Jennifer Swafford. My email address is Jay Swafford at vertex communications.com. We'd love to hear from you.
Great Thanks very much, Jennifer. Our next and final presenter is Andrew Preston. So via Cassini, Andrew is exploring new ways to reconnect research with the people it's meant to reach. Over to you, Andrew. Thank you. Betsy I don't know that I wrote that sentence. Sentence is really good. I'm going to be using that.
It's free. It's yours. I wrote it last night at like 1130. Thank you. Yeah let's see. So so I'm a researcher. I'm a physicist originally. And I think just about any researcher you'll talk about, talk to the reason they've historically or historically published in the journals that I published in was all down to the community.
You know, my collaborators were publishing those journals. Certainly my supervisors were. We knew that editors, your competitors are there all these sorts of things. There was a real sense of community around the journal, that's kind of, you know, over the last little while, evolved a lot with, you know, discovery tools like Google Scholar, et cetera you go to the journal lists now, even on this call today, you know, in the first two presentations, there's so much talk about AI and what it's doing.
And a lot of it is kind of drawing people away from the journal, whether it's on the consumption end, like we kind of heard with Kashmir or on the editorial side with manutuke. And I guess kind of the way we see it is that these changes are significantly impacting the relevance of journals going forward, and that is having an impact on the ability for, any given journal to attract the right authors, reviewers and editors to come along and contribute.
And so I guess our contention is that, counterintuitively, as AI gets more and more important and valuable, actually probably the most important thing to be thinking about is the humans behind the AI. And so you can think of as Cassini, think of Cassini as a way of trying to get back in touch with the humans behind, behind the AI. And what we've done is built a seminar platform, but a really good way of connecting with researchers and building a community around the research as you're connecting with.
So our seminar platform integrates with journals or a portfolio of journals to draw in a community of engaged authors, reviewers, and editors from around the world. We're then able to track and measure the impact of this engagement, showing how it drives submissions, submission citations, all these sorts of things kind of out of the box. And the way we built the platform with AI, et cetera does make it easy to do this in a hands off way.
Oh, there we go. The slides are back. So it's kind of the let's say problem solution statement. What is the product look like. So we're all in a Zoom webinar right now. Here's the Cassini version of a meeting. We're actually here wrapping around Zoom. And you've got your standard Zoom experience in the middle there.
But in this case, this is a seminar about acoustic and electric waves. In metamaterials. You can see the Zoom meeting, but down below you can also see the community of people who are in this meeting and involved. So, you know, you're in a webinar situation right now, you might not know who else is in the room. Even if it's a Zoom meeting, you might just have a list of names on the side.
But actually really important in this research context is knowing who's there with you, who's interested in this topic, why are they interested in this topic. And so we've put a lot of effort into, in this live kind of event situation, to make it possible to know exactly who's in the room with you and for you to kind of get to know them and, and ultimately connect with them.
And so this is a screenshot of the live event. But obviously behind the scenes we're doing a lot. So we have tools that will help you. Also defined as an organizer, the people that should be in this live event that might not know about it yet. So audience building these sorts of things as well. And it doesn't just end with the live event. You know, as a younger generation, the YouTube, TikTok generation of, of researchers kind of emerges.
There's a growing preprints for viewing. And so the idea is that for any given PDF, any given paper in a journal, you can get in the authors to give a talk, and there may or may not be a live event, but you also end up with a recording, something that an engaging video that people can come in and watch after the fact. And so you can think of this also as augmenting the PDF with video.
And it's not just the video. We do a lot to look inside what the speaker has spoken about, extract all of the slides, make them searchable, make them queryable by AI so you can ask any seminar question and of course any reference in the videos as well as extracted and connected to the literature. So it's very connected. And that connection to the literature is important. So I'm showing here an article page, the same article page for this PDF.
And you can see how we've been able to actually embed the seminar into the journal page. And we can do that kind of through an automatic one click Configuration for upcoming seminars. There's an option there to RSVP for seminars that have been held already. You can watch the recording, but we go beyond that in terms of integrating. So we will, you know, connect into tools like dimensions for discovery and EndNote for our reference management and all these tools, these videos, these seminars will appear and be discoverable.
So we're fully integrated into the scholarly ecosystem. Make building something really, really useful for researchers. So that's the product. What's the outcome we're showing you here Cassini pulse where members of that community, you know, they've engaged in the platform in various ways. And we can show how engaged they are. And so you can start to get an idea of who in your community is most engaged, might be interested in publishing, becoming a guest editor, these sorts of things.
And so kind of out of the box, as I said, these sorts of tools start to emerge. We kind wrap all this up, all these things that are happening. It's something we call the Cassini effect and what that is, is basically, as you build these communities on Cassini, we can show and measure for any journal that it will lead to an increase in high quality submissions and increase in citations relative to baseline downloads, and then also things like guest editors.
So if you're running special collections, it actually turns out to be a great way to find guest editors for those special collections and these sorts of things. So giving you here an example, a case study of a journal that started out as a Q2 title, publishing about 200 articles per year grew significantly over the months they built a community of, you know, eight, 800, maybe 1,000 people on Cassini is now Q1 growing rapidly really strong journal.
And so it's been great to see the global community that's been built around us and the engagement that's resulted. And I guess I'll just leave you with a vision or the idea here. AI is becoming more important, but the humans behind it are critical too. How can we build that community, build the human layer and integrate it back into the journal? So we're showing you here a journal that uses Cassini. We've shown you here on the left, the community.
And, you know, this should really be the thing that is what you come to the journal to discover. So I will end there. Great Thank you, Andrew. And now we've got about two minutes or so for questions. We've had a couple come in while folks were speaking. I'm going to start with this one here. So this one goes to Jonathan and Kashmir.
How do you balance broad distribution with protecting subscription and licensing models. Good question. I think ultimately, it's up to the publisher and their strategy and how they want to pursue it. So some publishers are looking for help in getting exposure to their content and being able to make sure that, like, they're exploring like that's even like just a new potential revenue channel.
So like there's some that are looking for that. And then there's others that are looking for more, you know, kind of access based controls. And so really we like I said, like we really see ourselves as like an ally for the publishers. And it's like we've got solutions and things that we're learning in the market, and we'll bring those as best we can and share those with you. And if you have opportunities that you've identified or that you want to explore, we can help you do that as well.
Nice then I've got a selfish one myself. I'd love to hear the story of the name Kashmir. Well, that's a funny story. We originally so my partners and I are huge fans of the T.V show Seinfeld. And we actually wanted to name the company. So George and Jerry and Kramer all have like their pseudo companies.
And we wanted, we wanted to call the company Vandelay. Like, I write Vandelay industries, but we didn't think that would go over very well. And so we my partner monk, had idea the idea of Kashmir for one of his previous businesses. And so we ended up we really liked that and kind of pulled it in and, and it feels really it feels like a good fit. Pun intended. Nice to the touch, as they say.
Yeah Thanks. Awesome related to that, same with Cassini. Andrew, where did that. Yeah where'd that. Where did that come from. What's the origin story there. It's Yeah. My co-founders, Ben and John. It comes out of their, I guess, startup name generator.
You know, we're all involved in a number of startups, but the idea is pick a famous scientist and change their name slightly until you can get the dotcom. So in this case, Giovanni Cassini was a famous astronomer. Discovered the rings around Saturn. Cassini was also a probe that went out to Saturn a few years ago. And so we changed his name slightly and got the.the.com. And actually, just one kind of nice related piece of information tied to that is Cassini was actually doing his work analyzing the rings of Saturn during a pandemic back in the 17th century or so.
And so we got started, during the pandemic. So that's very cool. Thank you. That was just coming from my curiosity there. We do have an attendee question for John. It's a question with a couple questions inside of it. Very meta. What is the manuscript format. That is, can you check both word files and PDF files that are submitted.
It's the first question. And then number two, are you checking against third party databases for example PubMed PubMed central, crossref, orcid et cetera. So it supports multi formats. It supports the word formats and also the PDFs. And you can just drag, drag and drop the your file in the system.
And it will automatically around the detection. So for the second question is that. I've, I don't know what this question means by the PubMed central because we have do you mean that do we compare the data with the central or where we compare with. The images or what? Could you be more specific.
We can wait to see who whoever answered that can provide some specificity. So probably let's park that one John and come back to it once that person replies. Oh wait, I'm thinking about citation analysis. Oh citation analysis. Basically, we're only checking the database, the citations from sources like from journals and the major affiliations and the corresponding affiliations and the corresponding authors and the first authors.
So we're matching all the authors if there's within one manuscript and if there are multiple, there are citation from one group of authors or from one author. They will give you alerts and if there's some many references are from one institution, they will give you alerts. And if there's a over citations from one journal and give you an alert to so.
And also we checked the relevance and to compare is basically the technology that we used to compare the keywords thing. So we don't compare with the completely with the third party databases. Also we, we, we compare with the crossref. So OK great. Thank you. And then my add on question for you is John, you had mentioned this is a project that's been in the works for a couple years.
Right and your editorial team at the current publisher where you reside, have been using this for a while. Are there plans to make this available outside of that publisher? Yes, that's why we're first of all, we I'm from a publisher and it's called Texas Tech science press. And firstly, we have a lot of challenges because there's a paper Mills are always targeting on the publishers with the small size, with a couple of other journals and easy to be infiltrate.
So so we, we feel like we may need a lot of workflows to fix the, a lot of loopholes on our, you know, the daily work. So and the paper Mills, we use a lot of strategies to testing your weakness. Like say if you are lack of checking at the final proof stage, they will change the data on the proof when they return the revision and they will change slightly, maybe one author or two.
And if you're lacking the pre-screening process and they will using the bulk submissions to take up all your time to take up all your human resources, and you don't have enough time for those good papers. So that's why we have an idea to invest the tool that we're using AI to shorten the time and to save and have a more accurate results to help us to make a decision.
So that's why that's how we started. And then right now we thought that this is a good tool. And then it could be a very product, a very good product. We can provide it to all other publishers or authors say whoever needs it. Thank you John. And then Jennifer, we've got one here for you. As expectations rise for more segmentation and more personalization with email.
How does vertex help publishing and society staff in particular, stay focused on their mission driven strategy, rather than that day to day execution. Well, our team is definitely very experienced in dealing with looking at the segmentation of audiences around the publications. And we're also looking at we're using the AI model for content. But we're also looking at as a data selection opportunity as well.
You know, we always know when people are clicking, we can follow those clicks onto your journal pages to see what other places they're going. That allows us to build out triggered messages. So we're not just sending these big bulk blasts to folks anymore. We're actually using their triggers and intelligence of what they're interested in, what they're reading and we're using that to build the segments out.
We also have keywords, topics, any of that can be sliced and diced based on the content that they are viewing from the emails themselves. Nice Thank you. Then I've got one from my own personal experience. This might be a little telling. So barriers to change, right? So your solutions are bringing a big change within organizations. And I know from firsthand experience that people like to hold on to the way they do things right.
So this human element element, to kind of pull that manual way out of people's hands, could you talk a little bit about how you help support your clients in that change. Absolutely I always like to say that I live in the tide change. So if the ocean is changing tide, I'm in it. And that's what we do with groups. But we're not into to disrupt too much. We come in, we assess what folks are doing.
We choose the wins or the things that are small, low hanging fruit that we can grab. And then we show those successes and then step into it easily. We don't need to do a whole seed change to make an email program really successful. But the baby steps can be really powerful and we make it easy. You know, it's not a matter of know, we were talking to humans. We're we're every each one of our clients has reps that help them really transform their program.
And so it's a little bit softer than coming in and saying, hey, we're going to rip this program out of your hands and make it a different way. Yeah, I mean, I hinted on LinkedIn there might be a puppy destroying my office, but luckily my kid was awake from her spring break, so she's puppy sitting but raising a puppy right now. I've learned that. I'm reminded of that when they're holding on to something trying to directly take it away is not the way right?
You got to come at it with a different approach. Well, it looks like we're right on time. So that's been the hour. A big Thanks to all of our panelists, and Thank you all for joining today as attendees. And as a related note, SSP does ask for a quick favor. We want your feedback. So please do consider taking just a few minutes to complete a session evaluation form.
It's invaluable to us. It's SSP and as a reminder, a recording of today's session will also be posted on the SSP on demand library in a few days. So Yeah, this concludes today's SSP innovation showcase. Thanks again, and have a great day everyone. Thank you. Bye Thank you. Thank you. Take care.
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