Surfacing Business-Critical Insights Quickly and Easily Using Smart Tools

Scott Burgess: Awesome welcome, George, just waiting for some folks to pop in.

Scott Burgess: And we'll give some. Give people a few minutes to get into the flow of things. But how's your day going so far, George?

George Avetisov: How's my day going

Scott Burgess: Yeah.

George Avetisov: Oh, it's lovely! I don't know what day it is, but we have a saying here, one up every day is Monday.

Scott Burgess: I love it.

Scott Burgess: I love it

Scott Burgess: I can. It feels it feels like that over here. Continu to. So I I hear you

George Avetisov: It's alright. It's end of quarter. It's exciting. I mean, when you work in tech SaaS, the end of the quarter is, like. It's like the holidays. But the complete opposite

Scott Burgess: Absolutely well. I'm excited, for you know. Thank you for taking the time to chat today, and I'm excited for our conversation. It's gonna be great to get into these topics together.

Scott Burgess: We are a proud one up customer as well. So we'll talk more about our experience with the work that you guys are doing. But yeah, very near and dear to our hearts in terms of the subject matter today. So today we'll be talking about you know, surfacing business, critical insights, and using the tools that we have today. There's so many great modern tools out there to

Scott Burgess: to help with these initiatives that we have with our companies so excited to dig in as we get into today we'll we'll you know. We'll share more about our companies, but mostly just wanted to talk about the topic at hand. And and you know, get into

Scott Burgess: into the subject matter. So with that said, I guess the biggest question we'll be answering today is, you know, is your team spending more time searching for fashion and using it. And I think that's

Scott Burgess: probably a topic that we've all experienced to some extent. The good news is that you're not alone. In that. I think every company experiences that one time or another. And this is quite interesting. Set here, just, you know. On average, we're wasting a lot of employees are wasting around 9 h per week. So it's kind of staggering. You know, folks looking for information that should be easily accessible. And that's where tools like

Scott Burgess: come in as well. So we'll talk more about that. And then, yeah, today, we're going to be talking about

Scott Burgess: You know, just the importance of access and how rapid access can really speed up just the flow of work.

Scott Burgess: We'll talk a little bit more about Continu.. And our world class LMS and our BI tools, and how we look at measurement as well as training and learning and information. We'll be speaking more about knowledge automation, and one of the great work that you're doing, George, at 1up, and then just overall the trends that we're seeing. Everyone's talking about. AI. And so how can we really

Scott Burgess: explore those trends together more? And just the sentiment around the usage of AI within companies. And it's obviously becoming a lot more widespread. So really exciting topics today. We'll dig in and get started with it all. Just a quick intro on myself. So my name is Scott. I'm the founder, and CEO here at Continu a modern learning management platform. So we help companies to centralize information into one place. I've been in this industry for

Scott Burgess: It's just over 20 years now, which makes me feel very old. But it's been really exciting to see just the whole trend of how learning happens and the speed of work. And how learning has evolved over time, and continues to evolve with these new technologies that we have at our disposal so excited to dig into that George would love to get a bit of intro from you, too.

George Avetisov: Yeah, thanks for having me, George, based out of New York City. In my past life I was the founder and CEO of Hyper Cyber Security Company, where I spent

George Avetisov: probably more than that statistic that you showed probably more than 9 hours searching for information. You know our team had a very technical sale. It was very enterprise facing, and, as you can imagine, we spent a lot of time looking through documentation, looking for all kinds of answers to technical questions. So you know, I am very familiar with this problem. I used to experience it, and I'm just really excited to be here talking about it.

Scott Burgess: Awesome. Well, happy to have you so. 1st question that we have for ourselves to to discuss

Scott Burgess: is, you know, what would your team accomplish if they could instantly access the exact information they need when they need it. And so, this is, you know, a really important question given what we know about how difficult it can be sometimes to find what people need and want to make sure that things are at people's fingertips, so George might turn this one over to you to get us started. You know. How? What do you think about this?

Scott Burgess: That's what you guys do

George Avetisov: Being in founder mode, I think closing more deals is the answer that comes to mind. You know, I think the answer is, it's gonna be different from department to department. But you know, with our focus being so heavily on, go to market teams, the number one

George Avetisov: outcome at the end of every one of these kinds. Of what if questions are, I could close more deals. I can win more customers. I can make the customers happier, and I think information retrieval, you know, searching for knowledge. This is a blocker to achieving that because most of the time the questions that customers are asking.

George Avetisov: You know, they're very fluid. They could be different. They could be unique to that situation, and getting an answer almost always involves a human right almost always requires distracting a human waiting for a human pulling in multiple humans or subject matter experts. So I think any level of automation here

George Avetisov: results in more customer happiness. And again, it might be different, based on different departments. But that's the immediate thing that comes to mind for me.

Scott Burgess: Yeah, absolutely. And I think that. You know, I love that you touched on the revenue aspect of it, because it is actually a mission critical problem.

Scott Burgess: You know, it does drive. It goes back to dollars. What's the cost of being like you said the humans that need to interact with helping answer questions. But then, what's the cost of us not being able to have the information that we need that could actually lead us to more sales or happier customers. I think, from my lens. I also look at it from, you know, happy employees and engaged employees.

Scott Burgess: If they're not hunting for things, and things are more accessible to them and they can find things, it's going to create more of a harmonious relationship with the information at hand. And they're going to get the information more readily. So for us to continue. Especially, we look at it from the lens of

Scott Burgess: yeah employee engagement. But then we also look at it from customer engagement. How can we make happier customers? And really make sure that we can get them the right information that they need, so that they can also be unblocked and unstuck in the work that they're doing. So. Yeah, mission critical. And I think it does really tie back to revenue. It ties back to, you know, revenue and also cost.

Scott Burgess: So you know, today, we're talking a bit more about like, what's the actual importance of it? I think there's some staggering data. That comes out of, you know, the real business impact. I mean, you mentioned the revenue aspect of it, which I think is key. But there's also things like decision, velocity. So how do we, you know, access information faster?

Scott Burgess: How do we get to decisions quicker and using your words, you know, using less humans in that process. So therefore, you know, cutting down the cost for the business as well as we do, that accuracy is something that you know, it is highly important. To be able to

Scott Burgess: use information that's actually accurate and relevant versus you know, folks hunting for the wrong thing or the wrong version, or the wrong files. So making sure the accuracy is, is really top of mind. Which leads to us being more competitive. Allowing us to have just just a better, faster way of of responding to customers, or

Scott Burgess: or, you know, in your use case even leading to revenue faster. And then, as I was saying, you know, it reduces the friction for employees. It really allows them to have just a happier environment to work in and allow them to get access to content more readily. And and you know again, just the time savings here, you know, by by

Scott Burgess: giving this information to our employees or to our customers, or

Scott Burgess: to whatever audience that we're serving. It's going to save time. And there, you know, in essence, it's going to save money. So this is pretty shocking to see some of these numbers? You know, 82% reporting difficulty finding information is just insane when you think about that.

Scott Burgess: So really quick, poll for everyone. You know, what is your organization's biggest challenge when it comes to accessing critical business information. So we're gonna open up the poll so everyone would love to hear from others in terms of what they say. I have my own ideas of what is on top of mind for me, I guess, George, while waiting for the answers to come in. What are your thoughts on like? What? How? What would you rate the highest for you

George Avetisov: Can I vote

Scott Burgess: Yeah, go for it.

George Avetisov: Alright, I would say the team members are relying on colleagues. You know, this is the less obvious

George Avetisov: effect. It's like a second order effect of knowledge management issues. And what happens is, you know, companies will often create lots of great documentation.

George Avetisov: And you think I've created documentation. And now I have all this stuff here, and people are just going to use it. But you often find that even with some of the best documented knowledge, and some of the best knowledge bases that we've seen. There's still this aspect of looping in a subject matter expert. Is this correct? Is this up to date? How do I know this is right?

George Avetisov: That's the second order impact of searching for information that ends up actually hurting the company. You're distracting people. You're constantly blowing up slack or Microsoft teams, or whatever you're using, they're getting distracted. And as someone coming in from a background in Enterprise sales.

George Avetisov: Those folks are always being pulled in different directions, right? Like even some of the smartest accounts. Executives are being pulled into customer questions. Their pre-sales. People are being pulled into their questions. It's constant right? So I would say that that second order effect to me is the worst of it.

George Avetisov: But everybody might have a different opinion, and I think it also differs based on your stage and size as a company

Scott Burgess: I'm sorry I couldn't agree more. I think that. And I I agree it's definitely it's it's definitely one of the

Scott Burgess: the items that stuck out to me personally were relying on colleagues. I think that's you know, even we look at it from our lens within onboarding. That's something that makes sure that information is accurate, making sure that you're getting the information at the right times. But there is a lot of reliance on other folks within those types of flows. And sometimes that's necessary.

Scott Burgess: But also it's something that can take a lot of time and can also decrease ramp times. If you are, you know uncertain about. Is this accurate? Is this the right information, you know? Is, is this the stuff that I really need to get into

Scott Burgess: so as the poll gets going

Scott Burgess: Kevin from our team, I don't know if we've closed the poll yet, and we've got those results coming through. So we've just gotten through. Some results. We actually have a tie for A and B, by the looks of it.

Scott Burgess: And so information is scattered across too many different systems. Finding specific data takes too long. And then, as you mentioned, George, team members rely on colleagues rather than self service. And so, unsurprising, I think all of the above are probably right. But any thoughts on these in terms of the poll poll answers any surprises there for you, George.

George Avetisov: I thought my option would be the winner. I guess I was off. Maybe I'm thinking too deeply in this, but I agree that you know, people when you ask them this question are probably gonna say, like finding specific answers takes too long. Right? That's the obvious surface level issue. So I'm not surprised that that's number one and I would say that that is a problem across virtually every business in the world. I've even talked to one person teams who are like I don't know where the stuff that I wrote exists, you know. So it's not surprising at all.

Scott Burgess: Yeah, absolutely. And I would also say, you know, one of our just one of our customers, before they became a customer, would say it said to us, you know, information is everywhere which means it's nowhere. And I think that's the problem that most companies experience is that

Scott Burgess: We sometimes have a bit of tool overload where things are scattered around the organization. It's hard to find and therefore to your point, you know, that's why we then bring in other team members to say, is this accurate? Is this the right updated information? So I think all of the above are accurate. But I would absolutely agree with the poll. So thanks everyone who

Scott Burgess: who submitted that

Scott Burgess: awesome. So we're gonna be talking a little bit about our companies. I think you know, one of the benefits of the work that we do is that it helps to address a lot of these problems, you know, from Continu's lens. We address it from the learning management side. So helping people centralize information, making sure that there is a single source of truth within the organization, and from the 1up side. You know, we'll talk more about this. But obviously knowledge automation and the fact that you can get access to information quickly and readily.

Scott Burgess: And really accurately. So just to give a bit more of an overview of or Continu as a modern learning management system. So we

Scott Burgess: exist to serve companies to help train their employees, their customers, their partners, where

Scott Burgess: consistently voted the number one enterprise. Lms, which we're really honored by our customers, consistently. Read us in that way. And we really, you know, are happy to serve a number of companies globally. With this problem. And it's a problem that we see in different shapes and forms, but is very similar across many industries, many organizations. So

Scott Burgess: we help companies to centralize learning. We help them to

Scott Burgess: get training and information into one place that can be the single source of truth and very easily accessible from anyone within the organization. We also help to surface information using tools like AI to ensure that recommended content is delivered at the point of need to the right individual at the right time.

Scott Burgess: And so we're really we've been doing this since 2012. We've been at this for a long time. We work really closely with our customers. We have a very consultative approach to the way that we build our software and as a result of that, we've been able to really look at this problem very closely. And see. You know how we can solve it. The other aspect of our platform is something I'm really excited to to really announce today and and speak about is

Scott Burgess: We've just launched what we call Continu Insights. And so with the

Scott Burgess: the ability for us to centralize learning into one place. It's very important that we can now give access to data and get it. Tell the stories around insights and and and analytics. And so today, we've launched our Bi tool, which is AI generated reporting that allows us to essentially ask questions, get results back based on the information that's within the Lms and surface. Really good good insights and stories about what's happening

Scott Burgess: within the organization, as it relates to the learning and training within our customer

Scott Burgess: partner, or even employee cohorts that we serve. So it's a really powerful feature and I'm really excited to launch it today. We're rolling it out to our customers over the next month. And it's something that will allow customers to really tell better stories around what they're they're they're seeing within the Lms itself. And we're really excited for it.

Scott Burgess: So with that said would love to learn more about about 1up and the work that you're doing, judge

George Avetisov: Yeah, absolutely. So.

George Avetisov: I'm a recipient of that pain that you described on the internal employee knowledge side. I've experienced it. I know the pain. I wish I had Continu at my last job.

George Avetisov: But you know, when we approach this problem of knowledge.

George Avetisov: automation, or knowledge management, whatever you want to call it. We look at it from a sales aspect. Right? So the sales team specifically, who deal with customer questions. More recently, this has become a questionnaire. You know a lot of our customers are people who have a customer. They're about to close the deal, and they get a 200 row questionnaire. Sometimes it's an Rfp, sometimes it's an excel word for excel, format, word, format web based questionnaire.

George Avetisov: These are constant. They're a huge source of pain. And what we wanted to do with 1up was to automate these specific use cases for sales teams. So today, our customer base is all over the globe. They use 1up to automate RFP responses, compliance questionnaires, and even customer questions, one off questions that come up in slack and Microsoft teams

George Avetisov: questions that come up in an email. It's a great way for people to get really fast answers to technical and product queries that their customers are asking. So that's a little bit about 1up. You're welcome to try it. You know, we've got great customers. Folks like fusion off, you know this is a good example of where does

George Avetisov: Does that employee time actually translate into? You know, if you have a teammate who's spending 4, 5, 6, or 12 hours, completing a 300 row RFP. That directly translates into time, loss, and money loss. Right? They could be doing something else. They should be doing something else. So

George Avetisov: This is, I think, a great stat. This is a great example of how these sales teams are actually realizing they can spend their time better focusing on customer activity and getting them out of the business of copy pasting answers. So that's how 1up is used. I would love for anyone who wants it to give it a try, free trials on the website. And again, you know, a good complement to how Continu's approaching and tackling this problem. But from a sales angle

Scott Burgess: Yeah, absolutely. And to give a quick plug, I guess for 1up we are happy customers of 1up. Our sales team uses it daily. And it really is a great complement to the work that we're doing. You know, we use our own LMS, of course we use our own product as a single source of truth for all knowledge within the company but our sales teams, our success. Teams love 1up for

Scott Burgess: really just surfacing information quickly. You know, if they're on a customer call, if they're looking at, maybe even pricing information. RFP questions all of the above. So it's a really great compliment. I think it really is.

Scott Burgess: It ties in the use of AI incredibly well, and it's a great resource for us. It's great, it's a great usage of, of, you know. Efficient use of AI. I think that's that's really, you know we looked at a lot of different tools to to do this, and very happy with our choice to use 1up so to, you know, really want to talk about a sort of last topic here, which is, you know, how do we both see the future of AI and and data

Scott Burgess: accessibility. It's a big topic and something that it's a question I get asked a lot when we're on customer calls, or even speaking to our team, you know, how do we see AI playing into our product? How do we see others using AI and that's something that you know. It's a question. I think a lot of businesses are asking today above, just

Scott Burgess: how can it be used? When should it be used? What's the right way to use it. This, every company is claiming to have some level of it. And so how do we really look at it through the lens of efficiency and and and really apply that to the work that we're doing today. So the question that I think we have on the next slide is related to you know.

Scott Burgess: how have users become more or less skeptical about large language models? And so for us, we've seen, you know, different different companies. And again, as you said earlier, George, it really depends on the company, the size, the department. But we've seen companies ask us this question through both lenses of. We really want AI. We really want things to enable with AI, or we

Scott Burgess: are skeptical of AI, and we don't want it to be part of everything that we're doing. And so I'm curious from your lens. You know. How? How are you seeing that with your customers? How do you see the future for that within folks adopting or adapting to the use of it. Or you know these elements within their organizations

George Avetisov: Is that a question for me

Scott Burgess: Yeah.

George Avetisov: So, this is an interesting one, because I pose this question all the time, especially when we talk to new Demos or new customers. It's what's your level of skepticism about LLMs, and I think you can bucket people into a couple of categories. There's folks who are 100% bought into the hype. They have unlimited budget so long as it

George Avetisov: It's in line with that hype cycle. There's others who have already tried different use cases for LLMs and feel jaded by some of these right? I think there was a lot of over-promising and under delivering, particularly on the part of LLM.

George Avetisov: Based providers not so much the foundational models. I think. You know, they're kind of insulated from this. But people who took the technology and wanted to fit it into different use cases, you know. One thing I heard from a customer recently was that they get on a call with some new AI provider every week, and it's the greatest demo they've ever seen. This stuff, Demos.

George Avetisov: really well, but then, when they try to implement it, whether it's for an Hr. Use case or a legal use case or whatever it

George Avetisov: always falls short. It's just like that last 5%, that last mile that's not quite there. So I think it's important to understand the level of skepticism. And you got to group people based on? Have they experienced the hype? Have they been jaded by a use case, or are they just still fully all in drinking the Kool-aid? I think those are very different scenarios. They're different in every industry. They're different for different use cases. For example,

George Avetisov: You know, the whole sale. SDR, AI use case is just collapsing in front of our eyes. It was one of the biggest use cases, you know, a year ago, 2 years ago, people were talking it up. We're gonna replace all the sales people in the next 18 months. There will be no salespeople.

George Avetisov: And if you're following the news today, you know, some of these Sdr AI companies are having a rough go, and I'm not saying anything bad about this technology. I'm just saying that's a perfect example of a used case that was really hyped up a couple of years later is, you know, people are scratching their heads and saying, what were we talking about? Right? So.

George Avetisov: Yeah, I think skepticism is different, based on industry, maturity use cases. I don't think there's a straight answer for that. And you just gotta ask people how they feel

Scott Burgess: Yeah, absolutely. I couldn't agree more. I think there's a lot of gimmicky AI out there. There's a lot of box-checking that. I think we've seen, too, in our industry and in other industries, even even as folks that are purchasing software. And you're right in saying that a lot of this Demos really? Well, and it's a little bit of of

Scott Burgess: you know, you don't know it until you actually use it. And so for us at least the lens that we look at whenever we're implementing anything that relates to AI is we look at it through the lens of how can we be more efficient and effective? And how can we enrich the experience? And so for us, a lot of it is as well as it is, how can we?

Scott Burgess: How can we still have the human element of learning? How can we still ensure that there's that human touch in everything that we do? Because I I think there's

Scott Burgess: I don't think that we're trying to replace the human element. But we wanna make it more effective and efficient for the end user. So from a Contin lens, we look at that through. How do we surface information to users through recommendations? Well, how do we make the authoring experience better for administrators, so that they can easily author content or easily automate the content to the right people. The right times. I think those those use cases and those benefits

Scott Burgess: are really tangible, and they actually do save time. It saves money. It creates a better experience, it creates more engagement. It brings people back to the Lms and it really does support the use cases around

Scott Burgess: the reasoning for these tools, which is time saving and efficiency. And so I do agree, though, that there's a lot of tools out there that also claim to do things that might not really be useful, and I always caution folks to look at it, not just to implement something with AI for AI sake.

Scott Burgess: But how do we? How do we implement something that's really gonna solve and have the benefits to the solution that we're trying to, you know. Solve here, and that's something that I think is really key for when you're procuring software.

Scott Burgess: and when you're going through a demo really testing to see how that that would work for you and what those use cases could can be so I think we might head back to a slide on

Scott Burgess: Just our future AI slide. You know how how we're

Scott Burgess: You know, thinking about that, I guess.

Scott Burgess: as we look through that lens of efficiency and effectiveness and really driving end results here.

Scott Burgess: wanting to make sure that you know we're also looking to the future of how that will be implemented, I think, with 1up. You know. Obviously, you're surfacing information in real time. How do you think that grows for you? And and how are you guys thinking about that in terms of that that future state of of data and and information, knowledge, accessibility

George Avetisov: Yeah, we're big believers in formatting and normalizing data. You know, I think a lot of people neglect these systems. Just how different all of the data is it

George Avetisov: really is. And they don't

George Avetisov: understand the nuances between some of these formats and data structures and even things like images. You know.

George Avetisov: How. How do you create one uniform handler for all of this? You don't. You have to really understand? What are you ingesting?

George Avetisov: Who is uploading it? What is their intent? What is the output that they expect? This stuff is different from department to department. It's different, based on document, type, knowledge, source type output type. I'm a genuine believer that

George Avetisov: these information retrieval systems will very much be different from department to department.

George Avetisov: I'll probably get a lot of stuff for I I get a lot of heat for this and the founder and VC kind of circles that I that I'm in because they want to believe in this kind of

George Avetisov: one information search system to rule them all. But if you actually drill down into it, you realize that the nuances between these departments are so wide and so different that

George Avetisov: it almost doesn't make sense to have one single retrieval system. And I think that that's true of all software. But in this case, when it comes to AI, we tend to forget for whatever reason. So I think that we're gonna see, we're gonna continue to go deep on this last mile problem. And for us, that last mile problem is like you like, I just told you, it's formatting. It's nuanced data types. It's, you know, things like images, structures that we haven't seen before. So

George Avetisov: That's where we're going. I think a lot of other teams who do dig double click on that. They're going to benefit as well

Scott Burgess: Yeah. Oh, I couldn't agree more. I think that's, I think, drilling down in that way and being really great at that. That one problem solved is really really important.

Scott Burgess: for us. We look at it through the lens of, you know, we talked about our release of AI insights today and the ability for us to surface data more readily to our customers, I think for us, especially in L&D. One of the biggest problems that we see is that everyone has a nuanced problem. When it comes to data, every company looks at it differently. Every company has different needs

Scott Burgess: around it. So for us, we're looking at it through the lens of how we can help surface business, critical insights that will help drive decision making? And how can we do that through the lens of learning and training? And so that's where we're really focused right now is, how can we be useful for our administrators or folks that need access to information. We also believe that

Scott Burgess: you know, the future of learning is to really meet the learner and meet the administrator where they are versus it being a destination. And so we believe that AI can play a big role in that in terms of bringing those insights to the end user or the end. Whoever needs to consume the data themselves. And so that's a big focus for us right now in the near term.

Scott Burgess: I would say that we also look at learning to the lens of it needs to be human, you know, learning and training and information, especially knowledge transfer. There has to be some human intervention. There it is, we all learn, in a sort of multimodal approach.

Scott Burgess: and so making sure that there is a really

Scott Burgess: big human touch and element to it. But making that human element more effective and efficient is the one that we have? We look at AI. So where does that play a role for us? It's.

Scott Burgess: you know, better authoring of content, allowing administrators to author it quickly and effectively and accurately. It's looking at surfacing information to the right people, the right times. And then it's looking at measurement. How do we measure that effectively, making sure that we have really digestible information, insights that can drive that experience. And so the future, we see it being really bright when it comes to

Scott Burgess: tying in new technologies like AI with the single source of truth in Continu but I would also say that it's not a single. It's not a silver bullet, you know. It's a lot of people, I think, like you said a lot of venture capitalists. There's a lot of buzz out there around AI being this

Scott Burgess: silver bullet that's going to solve everything for everyone. I think so. It needs to be applied in the right way, and it needs to be leveraged in the right way. That will really drive outcomes and look at. Look at it through like what are the problems. We're actually solving versus just

Scott Burgess: adapting to AI for AI sake. As you said before, earlier, just around things demoing well, but not having a real world sort of use case

George Avetisov: Yeah, you don't want to build AI for AI sake.

Scott Burgess: Exactly exactly. So it's really really important to look at these things, especially as you're procuring software through the lens of like, what are we actually solving? And how does that happen? It's a tool to be used? And how do we use it? More effectively?

Scott Burgess: Awesome? Well, I guess, moving, moving back down. You know, I wanted to really open it up to the audience. Do you know any questions that we can ask? We can help answer any things that we can address from the conversation today, or just things that you're thinking about within your organizations.

Scott Burgess: So we'll open up to the audience.

Scott Burgess: As we do that, George. Anything on your side that you want us to add around

George Avetisov: Knowledge, retrieval.

George Avetisov: I think that I have a controversial take on this, and don't flame me for this, but I think that what a lot of people don't realize is knowledge. Management is not a hair on fire problem.

George Avetisov: When you talk to many of these organizations, they say it's a problem.

George Avetisov: They'll express the pain of it. They're aware of it.

George Avetisov: But it's not a hair on fire problem, for you know.

George Avetisov: compared with some of the other things that they're trying to solve. I think the reason for this is people have not been able to marry a budget line item with knowledge management. I think that you know, when you talk to some of these teams. Sometimes it's budgeted, sometimes it isn't, sometimes there's an initiative, sometimes there isn't. They all say the pain of it, like nobody says, Oh, we have no knowledge management problem. They all say that they do.

George Avetisov: but it's not always like what I would consider a hair on fire problem where they are out and buying something for it. So I think that's an interesting concept. I don't have an answer to that. But what I would say is, what I like. That Continu does

George Avetisov: is focusing very specifically on these use cases, because in focusing on use cases and departments and pain points. It's much easier to turn that into or translate it into a hair on fire problem and an actual budget line item. So I love what you all are doing. I would say that for those who are trying to buy this material on the buyer side, on the customer side.

George Avetisov: You know. Think about how you express this to your leadership team as a hair on fire problem. And yeah, that would be my take. Let me know if I'm way off

Scott Burgess: Yeah, I think you're spot on. I think it's not a hair on fire problem until it becomes a hair on fire problem. And then it's almost too late. Right? And so and that's when the pain is really felt and folks are trying to solve it. And and and so I think it is important to surface these things earlier. Because it is like we've talked about is a business critical challenge

Scott Burgess: and something that costs a lot of resources. It's something that can cost engagement of employees or customers and is something that can be very detrimental.

Scott Burgess: If not solved correctly and early, and so I would totally agree. I think that's that. How we see it, too, is that it's not here, and until it becomes one. So we got it. We got one question come through so far in our Q. And a question is, a question of the product should have the same answers across the company, but often an individual's interpretation gets in the way. How do you solve for the universal answer? And this comes back to what you were saying earlier, George, around.

Scott Burgess: You know, bringing in multiple colleagues to solve a question. And making sure that that's accurate. Obviously, 1up solves this through the tools that you're building. But what do you think about this? So, yeah, how do you solve that universal answer across the company from your

George Avetisov: So we think answers get generated in a number of ways we consider.

George Avetisov: Let's just say there's 2 types of sources. There are unstructured data sources that can help generate a new answer for the 1st time ever. And there are previous answers. And if something was a previous answer that was considered authoritative.

George Avetisov: Let's say, for example, it might have been upvoted, or someone saved it as an answer to be used that should be treated with a higher level of authority than a newly generated response. So the way we tackle this problem is, we have, you know, we inform users, if you like an answer. You want this to be the authoritative answer.

George Avetisov: Specify that, and we make it easy for them to do that in our system. And then, if an answer is generated entirely on the fly for the 1st time, that might be a new phrasing, that might be something completely different. So again.

George Avetisov: it is going to be different, for every question. Answers are always different, based on the phrasing of the question. But if you have an answer library that's built off of previously uploaded or saved responses. That's where you're gonna start to see those repeat, perfectly phrased answers that you're referring to in your question.

Scott Burgess: Yeah, I love that. I love that. And we've seen that firsthand as users of the product. But also you know, we see this inside the company ourselves. Just using Continu, we, we, you know, create single sources of truth for information and knowledge, and that that allows folks to to make sure that there is

Scott Burgess: that single source of knowledge that they can reference back. So you know, if it's a, it's a question. Maybe it's a question on something within the organization, or some policy change or things there. We can help to answer those questions by utilizing Continu so. I think again.

Scott Burgess: really great partnership, that we both have terms of both of our products solving these things in different ways. But it comes back to like you said, making sure there is some human intervention. I think that that's something that we also have to get used to.

Scott Burgess: It's not to say it's not a silver bullet. These questions aren't just going to be answered and forgotten about. And then that's gospel. We have to make sure that we're fact checking. But there are ways for us to make sure that that is the sort of certified answer that users can get back into. So we have a couple of the questions that came through. One from Laura that came came in

Scott Burgess: around, you know, when our executives ask if training is actually helping the business, I panic because I can't quickly pull the right data. We have the information somewhere, but it takes hours to find and compile. How do we better prepare for these on the spot requests about training impact? And so this is exactly what we're building with Continu Insights is, how can we surface the right information and the right data in real time

Scott Burgess: and allow people to solve these questions that they have, and then go a step further and create a digest that can be sent to management or other users that can be surfaced, let's say weekly or daily, so they can always have data at their fingertips. I think it also comes back to making sure that you're measuring the right things and putting in the right information into the LMS or into the solutions that you're using. That will allow you to make sure that you're really measuring

Scott Burgess: the right information at the right times. And so for us, this is a problem that we're constantly looking at, because, as I mentioned earlier. Every company has their own way of looking at data and looking at the information that they want to digest. And so for us, it's an ongoing question and ways that we're trying to solve with Continu Insights and other

Scott Burgess: ways that we collect data. The other aspect of this is also making sure that you're segmenting content and information for the right audiences. And so that's something that we do to continue as well as making sure that we are right.

Scott Burgess: Buckets of information go to the right people at the right times, and that will also allow you to measure the impact of that content because folks aren't looking for things everywhere. They're getting the right information at the right times, and therefore you can measure that more accurately. The other question that we just got through. So I think, it is more for you, George, which is our reps are constantly during the headlights when prospects

Scott Burgess: ask specific questions during Demos. They can't find you very quickly across the mess of documents and and everything you know, badly or or promise to follow up what can be done to improve the flow without having a hundred sales sheets to pass through

George Avetisov: Yeah. So I think less is more, is the answer to this question. I'll give you two parts number one. Some of our best customers who generate thousands of answers a week, who do hundreds of RFPs. They have many, many users talking to 1up constantly. Their knowledge base is actually pretty small.

George Avetisov: they have a very much, a less is more attitude. That's where they are able to not only control the inputs more easily, but they're also able to really see the value of those outputs and see kind of the repetition in those great answers. So I would say, stop thinking about pulling in your whole company's knowledge into one place. Start focusing on what is the knowledge that matters in this moment, this quarter this year, right now, and you'll be surprised how much smaller that is than what you're thinking.

George Avetisov: The other thing I would say is, make your content. AI ready.

George Avetisov: People do not do this enough.

George Avetisov: There is a level of quality

George Avetisov: that you want to adhere to.

George Avetisov: That makes your content readable by LLMs. I think we're seeing this right now with websites that are trying to make their content indexable, or easier to index or easier to read. For LLMs. You should be doing the same with your documents. Stop using fancy images, you know, when text will do. Stop making weird kinds of formatting. And you know, let's just say.

George Avetisov: focus on readability.

George Avetisov: Good, clean text.

George Avetisov: It doesn't need to be fancy. It just needs to be read by a system easily. So I think creating content for the robot is a new trend that we're going to see. And you know, we're always talking about creating content. That's for humans. You're going to see a lot of people trying to create content for the LLMs to read. And I think that's really important. Otherwise your great content won't be readable. It won't be an indexed role, and it just won't make its way to the output that you're hoping for.

Scott Burgess: That's awesome. Yeah, that makes a lot of sense. And I think that's something that's very critical. Probably another topic that we can talk about explicitly, because it's just such a big one. Especially as we look at that from the training lens as well as from the work that you're doing on the sales and support lens, too. So

Scott Burgess: excellent! Well, thank you all for the great questions that were, it was really great to be able to dig into those I guess the key takeaways, you know, as we, as we, you know, get to. So wrapping up here is

Scott Burgess: I guess there's just 3 points that we covered today. So you know, making information available is a competitive advantage. It allows you to access information when needed. It allows you to develop your teams or your customers in the right ways. It really is a cost savings as well as a revenue generating, you know, initiative for you in your business.

Scott Burgess: Modern tools like 1up and Continu are eliminating these burdens today. They're allowing people to create a single source of truth information to allow people to ask questions and get answers in real time. And then, lastly, but definitely, not least, is just the power of AI. You know we're seeing AI being adopted more readily across

Scott Burgess: all industries and many products. And it has such a broad use case and things like that can be really automated and improved through the use of AI. And so we discussed, you know, some of the benefits of it today. As well as just some of the things that George just mentioned around making sure that content and information is also readily searchable and indexable by these Llms.

Scott Burgess: And so I think, yeah, hopefully, there's some good key takeaways from all of you from the call today. We really appreciate everyone tuning in today. And George really appreciate your time. As the next step we'll be sending out these slides. Everyone can have access to them. See some of the resources and the links that we've also talked about as well. Encourage you all to check out 1up and also Continu shameless plug there. But yeah, thank you all for the tuning in today, George. Thanks again for the time

George Avetisov: Awesome. I always love these. Thank you for having me. And if you need anything email, george@1up.ai or go to our website. Hit that free trial button. You'll be up and running in 5 min.

Scott Burgess: Amazing. Thanks. George, thanks. Everyone.

George Avetisov: Take care!