The Truth About Company Knowledge. This Is What You're Missing.

**[00:00:00]** Hello everyone, my name is Armando Perez-Carreno, and welcome to the Web Talk Show. Today with us is Daniel Fallmann, he's the CEO and founder of Mindbreeze. Welcome Daniel, how are you? Thank you, I'm fine. Thanks for having me. Oh, it is my pleasure. I'm doing very well. Thank you for asking. Mindbreeze, I've read about recently. You are doing some very interesting things in the space. I have a lot of questions, but before we dive into all the technical and fun stuff, can you please give our listeners a brief introduction as to what Mindbreeze is, and also how you got to where you are right now? Yeah, I mean, you know, I I I founded the company back in 2005. Back then it was around everything was around enterprise search. So, how can you combine tons of structured, unstructured data from all around the enterprises to kind of help the the end user find relevant information, relevant documents. That's where we are coming from. And still today, right, the key the key essence of what we do as Mindbreeze is we really help to build this intelligent enterprise for our customers, where we combine all the relevant information, and and support their users, support their agents, support their AI to to have all the relevant context in place to really take well-informed decisions, right? So, well-informed decisions changed over time from things that were important for users to nowadays well-informed context and information and decisions are relevant for agents as well. And everybody's talking about agents, right? Yes. Yes. Oh, that's that's very interesting because many people are just starting the conversation about the company brain and the knowledge of the company because they're hearing it as a **[00:02:00]** necessity for the agents and the LLMs to be able to have context about what they're doing. So, for a lot of them, that's the first time they've heard of it, but you've been in this business for a while, even before all the LLM craze and and gathering that knowledge for enterprises. So, can you bring us to if I'm maybe I'm a regular person, I don't have a business or maybe I have a business, but it's a small or medium business, not enterprise grade. What what are what what have the enterprise and corporations been doing for all these years to consolidate their knowledge? What did search enterprise search look like before we got into all the the LLM-based world? Yeah, I think, you know, this is um AI didn't didn't change a lot in our space. In reality, it it just helped to speed up understanding information, right? I think one of the the biggest misconceptions today is like AI projects failing because of of models or hallucination. I think in reality that the the model in the AI stack is not the problem at all. I think what um what is crucial is context and the trusted relevant information. Yeah? That those uh methods and and processes really uh take the knowledge from. And I think that this is exactly where the enterprise AI search, as it's it's more more called these days, really kicks in, right? I think what always has been outstanding with enterprise search and even 20 years later now with enterprise AI search and **[00:04:00]** combining information is that the context of information is is still needed for everything we do, yeah? Um and and I think that's really the key, right? The challenge is helping AI understand the enterprise, yeah? And tools like Mindbreeze do an outstanding job in exactly that, yeah? And I think that's also uh where where many organizations, customers, partners today really discover that this enterprise AI is fundamentally a knowledge problem, I would say, and it's not the model problem at all. You have the knowledge as an organization already. You have the experts, you have the subject matter experts, you have uh uh processes that have done a great job for you as an organization for potentially decades, right? That you have further refined over time. And now you transform that knowledge into the AI world. But still make sure you use the existing knowledge for the transformation, yeah? Because that's crucial, right? That the AI works best if it has the knowledge and the context, yeah? And it understands the business domain, yeah? Everything else, right? You don't need something that just generates a better text. That's not the challenge. You need something that understands really your business and really talks into processes, workflows. Yes. Yes. That is very clear. A even with basic examples, I did a talk recently at a like a trucking conference and I was I was showing people like, yes, you can ask just a chat GPT or whatever model you want, Claude, Gemini, Grok, **[00:06:00]** uh what is the torque spec on a specific engine's part? And it might give it to you, but it also might make it up because it's not like publicly known information. But if you have the right context connected to the model and it has the right manuals connected to it, then it could give you an accurate response, right? Just bringing it to like a very basic, perhaps not enterprise level, right? I think what what you're saying is spot on. It's a knowledge project to to get someone ready to be able to actually take advantage of these tools. And correct me if I'm wrong, some people might actually, right now, just need to fix that knowledge problem regardless of even if they decide to use AI now or in the future. Exactly. Yeah, exactly. That's what you say, right? I think that the the the the question down-to-earth is really is the real bottleneck that we are facing here. Is it the AI piece or is it access to knowledge? And I would argue clearly access to knowledge is the thing, right? Because, as you said, open my eye, Lord, yeah, uh Mistral and all the others, right? I think they are doing an outstanding job in everything that you would expect from models, potentially even specialized models in the future, large language models currently, of course, yeah. Uh that's where the scaling worldwide, so to say, comes from. But I think I would say that the real bottleneck is really knowledge, yeah. I think that the the the the the world, right? Is is rapidly moving towards a future where everybody has access to powerful AI models. Yeah? But the the the question it is no longer who or which organization has **[00:08:00]** AI. The question is who can provide AI with the best understanding of their business and equip it with the best understanding of their business. And most organizations, I would say, already have the expertise they need in-house. They have the subject matter experts. They have all this information in different sources. Or let's even call it silos, right? Uh but those applications were not designed to provide information proactively in the best possible way. Um those applications were initially designed to trigger workflows, to store information, to version information. Yeah? For you to work on very specific tasks. But now, this information in those applications, with all the context in there, yeah? Is needed by AI. Yeah? And I think that that that this is really the the the the the the important piece of what organizations should discuss and put their focus on. Yeah? Um uh uh getting that well done. And once you have this foundation, yeah? Uh you can put on that foundation the rest. Yes. That's the way to go. It's And it's not only corporations and enterprise any size business, at the end of the day, needs to, as you said, they already have the knowledge. Somebody has the knowledge. So, either it's siloed in different systems, like you were saying, or it might be siloed in someone's head. It might be you have that one employee that knows everything about a process, and when they're out, then nobody knows what's going on. So, the information is there, but but it's not really readable for **[00:10:00]** not to say the AI, the business. Like, if if one of those people in your company leaves for the day or for a month or for whatever, and your business slows down or stops, then you have a big dependency problem. That information should be knowledge that the business has. It Exactly. Exactly, and that's that's that's what what you mentioned, right? I would argue as the augmented employee. Yeah? So, you have the subject matter experts, as you explained, in the organization. Now, those subject matter experts are very good solving specific tasks. Like, if you have a legal service team, right? It's is quite likely that if you hand over an NDA to the legal service team, yeah? They immediately can tell you clauses that that put risk to the company. Like, for example, any unlimited cap discussion or orally disclosed information that is almost uncontrollable what was orally discussed, right? Uh things like that, yeah? And they pinpoint you to exactly those critical clauses, yeah? Now, you can automate that with AI, right? You automate those tasks to make it scalable for the organization. Now, those tasks with the subject matter expertise, with your data, with the knowledge of what you as an organization need again and again, you make that scalable. So, you try to make this one subject matter expert in some of their subtasks scalable for the whole organization. Yeah? And this is then um what we call the augmented employee, right? Because you make a computer scientist like myself, right? You enable such a person um to **[00:12:00]** automatically and on its own scan, but do pre-checks on contractual clauses without a subject matter expert really needed. You take away manual task, and you organization you really in the organization you scale that uh knowledge in workflows, in processes, and in general for the whole organization. I think that's really key, and that's that's the real power, I would say, of those augmented employees. That makes perfect sense. It's not only let me automate workflows and all the things we hear about, it's also simple though simple things like having the right knowledge in the system so that it can flag specific situations automatically even for those who are not experts in that particular field. And that also if you have workers at different levels, like maybe you have factory workers, and then you have executive workers, and you have all sorts of different employees in organization, many times there has to be communication, you have to stop what someone is doing so they can answer a question to someone else because they're the expert, but if you have it the way you're explaining, then anyone can get the information they need quickly and then only interrupt the subject matter expert which might cost more for the company in regards to time and efficiency. Um only when when really needed. Right. I think that the the impact is is tremendous, right? So, as you say, you know, you can speed up certain processes, but I think it it also dramatically accelerates decision-making. Yeah. Most of the decision-making in **[00:14:00]** organizations is always based on facts on information. You speed that up up by by by a factor, right? Um troubleshooting tasks, prototyping tasks, process optimization tasks, process transformation tasks, yeah. Cross-functional collaboration, a very important piece, right? Most of the time uh uh you have to wait for teams to come together this you because you are missing a very specific expertise. As you can scale more more expertise, yeah, um it helps you to also speed up this cross-functional collaboration tasks. And I would say implementation speed at the end of the day, right? Implementing change, organizational change, new processes, uh uh trans- transformational tasks, right? Uh they're totally different totally different game. Yes. Have you seen with your experience of integrating knowledge and and enterprise search into an organization that their onboarding for new employees is more efficient and Yeah. maybe even affects how long those employees last in the company. Yeah, that is that is of course one of our one of our clear areas of focus as Mind Precies, right? Onboarding employees can benefit from tools like ours in multiple ways. One is understanding policies hands-on. What do I mean by that, right? You know you would love as a new employee you often know I would love to do this and this and this, but is it in is it aligned with our corporate policies? In very large organizations you you have thousands if not hundreds of thousands **[00:16:00]** of policies or parts of policies, right? So you it's typically hard to know if whatever you try to do which worked at a company before for example still would work for this company because of the given policies. Mind Precies or tools like ours can immediately support you with it. Moreover finding standard operating procedures, finding best practices, right? Very important because only if you find it you can teach yourself and speed up yourself, yeah, to be faster productive for the organization. That's another item. And the at the end of the day it's not only finding information, it's finding experts. Yeah. Tools like ours, so products like ours, right? Know based on the information that the people edit, that the people create, who is an who is likely to be an expert in which topics. Yeah. So you can also hand over, yeah, who are experts in the organization for certain topics to new employees, which helps them to find the right people in the organization, which sounds, you know, which sounds funny if you you feel a small organization because they don't typically have that problem. Everybody knows each other, but the company that has 10,000, 50,000, 100,000, or a million employees, right? For them, it matters to find the right skilled person to help them with questions or tasks they're trying to do. And And that's That's a perfect fit. Mhm. Yes, that is super interesting. Because if you didn't have that, then you would have to ask Peter, who would say, "Oh, yeah, I think I know a person in this department." And then Peter had to stop what he's doing and then ask that other person via email or Slack or Teams or whatever. And then that other person maybe says, "Oh, no, yeah, I sort **[00:18:00]** of do that, but actually it's Jessica over there." And they just bounce around. And so you already interrupted 15 people to get what you wanted. versus Absolutely. I would I would absolutely agree to that, right? And I would even add, you can only ask Peter if he is one of those who is longer in the organization already, which at very um at organizations that grow very fast, right? The this uh uh this need is even uh more important and more demand There is more demand uh in that organization if it's a fast-growing organization, yeah? Because it's quite likely that whoever you ask there close to you, they might be quite new in the organization as well, right? Um And that's where you then even more need tools like ours. Yes. That is an excellent point. These These A lot of companies just just grow so fast. It's actually strange when I talk with someone and they say, "Oh, yeah, I've been 30 years in the company." I'm like, "Wow, that is a milestone." Nowadays, you don't really hear that. And so for sure, that is definitely something that happens. And and then also, if you knew to ask the right person, like maybe you asked completely the wrong person and they just send you through a rabbit hole and and you didn't get what you're looking for. So, how does something like this work in practice? They they're in the office, they might have a question, they want to query the information about the company. Do they type it typically? They type it in? Is voice search or something like that a thing? How does that work? Well, it's a it's a it's a combination, right? Um um I I think uh 3 years ago, the typical user was uh the employee. Yeah? The typical user was the employee typing in a natural **[00:20:00]** language question, uh uploading an image, and and asking questions to that image, uploading documents, asking questions around information in the enterprise connected to those uh uh assets you uploaded. Um that was the classic way, right? More and more we see now, and that's the that's for sure also, thanks God, to AI and all of what was done in the last 3 years and and uh uh we live in this AI age, right? And uh now people understand what information and knowledge is capable of doing if you use it uh in as a relevant asset in your organization and really try to embed it everywhere. What I mean by that is, for example, uh uh field service engineers, right? Um we see more and more companies integrating uh uh our product into their field service applications, totally seamless. Yeah? So that the workers do not even they do not even know that behind the scenes somebody is collecting the information for them, preparing the information. But in reality, that's is really done by Mindbreeze then. Yeah? And so it's embedding embedding products like Mindbreeze embedding our technology in other applications they use to make them stronger, right? More efficient, better, to the point. And the other thing that we have seen over the last few years is a tremendous rise in in queries from agents. Yeah? So it's not only the users asking with voice, natural language, typing in queries, uploading material and asking question around it. It's really agents. Agents that say, I would have a task to do because my user told me or another another agent told me to do something, right? And they need information collected, but collected in a way that **[00:22:00]** of course context sensitive. Yeah? So with a context of the work that you're trying to do with the access rights of the asking users or the asking agents in place and enforced because that's crucial, right? The agent should only see what you would be able to see if it runs impersonated as you said to say. Yeah? And it should definitely not have access to everything because the access rights are there for very good reasons and they need to be enforced. And we see more and more queries and inquiries from agents against our services. So the real booster now for why the the queries per second and the queries annually grow like hell at our customers is agents asking Mindbreeze all those questions. I you bring up an excellent point that I that I would like you if if if you could dive a little deeper into which is access control access restrictions. A good friend of mine always says since we started all this conversation, you have to treat any AI surface as another employee. The same way you would onboard an employee in an enterprise where you would give them their own account and their own email and their own role with specific capabilities and access to certain information. You don't just hand blanket access to an AI to the system. You you rather give it as if it was a user with logs, with everything, so that it can just see what it would have been possible for that person to see and and different levels, right? So, and what you're talking about right now that's something a lot of companies, especially smaller companies, forget to to get into. So, the the question becomes um how **[00:24:00]** should should companies think about this uh in in a in a clear easy to understand way where it's like okay, I I'm not giving Cloud access to my enterprise system. That's a lot of people have fears of that when they hear about it, they're like how how am I not going to give it access to it? So, how does that work? How how do you implement something like My English School or any other system so such that the CEO and CRO can can feel comfortable knowing that their information is going to be safe while still accessible to the right people or the right agents? Absolutely. So, so I think at the end of the day it all goes down to to governance and trust, right? Um I think that uh governance in general is is foundational for enterprise AI, in my opinion, yeah? No way around it. And especially in in regulated industries, right? So, so customers expect auditability. con- con- contextual access control, which means really that the user is authenticated and the user gets authorized results back, information back from sources all over the enterprise. Yeah? Typically, this is done, the authentication piece, with single sign-on, right? You have Entra or Okta or other tools where you you solve of the authentication piece and then every source typically has their own access rights. So, tools like ours have to understand the access control uh checking that the sources do and make sure that every data, you know, we have this common database, this knowledge base that we build, you normally refer to as an index. Yeah? In our case, it's a hybrid index. It's a It's an It's index structures and vector indices, of course, plus also knowledge graph information built into the one structure, which makes us very unique. **[00:26:00]** And that means that for all those assets in those indices, you have to make sure that access control is enforced. So, then you have this contextual access control, right? And then you have approval workflows, traceability, uh policy alignment, and and all of that the security integration into your enterprise systems well done. Yeah? And that comes with experience, right? That that really comes with experience. I mean, I always have to say that uh it is really cool how fast-paced this world is today, and I love speed. I love change, right? Uh that's really my DNA. If something moves, it's great for me, right? Um and still I have to say, governance and trust is something that comes from experience. So, the last 21 years that we have worked on Mindbreeze being the knowledge that that the foundational knowledge hub in some of the largest organizations worldwide, we typically refer to as the knowledge backbone, right? Um uh this is only doable with experience and and governance and trust in place. This is something that you cannot shortcut uh uh by a factor, right? Um this needs to be done iterative. You can't say, "Hey, you know, I now received a billion venture capital. Uh that's why now I'm from a governance and trust perspective the absolute non plus ultra out there, yeah?" That's just not the case, right? Uh this comes from experience, from understanding the sources, from doing things, I would say excellent and professional instead of only fast. And still in our industry, there are things that can be done extremely fast with high quality, but there are things that just need time, yeah? To be to be very **[00:28:00]** well designed. And I think the whole layer of governance trust with Mindbreeze, this credibility that we have built over decades now, um this is really what we stand for, right? That's the reason why many of the Fortune 500s, very large organizations work with us and love to work with us, yeah? Uh because it's just this this we we I think we have just built a great brand for exactly what we do. And many people don't realize the importance of of governance. Like it's a because it's moving so fast, it's easy to want to hop into it, but as you say, it's it's very important to sometimes just take a step back and say, "Okay, how would I do this without AI? What would I do if I wanted just people to access this information? If I just wanted to build an enterprise search for my organization, how would that work? Because you would still use vector stores and knowledge graphs and things like that even if you weren't using AI to query it. So, how would you do it without AI? And now you're going to start to find a lot of edge cases and and places where oh, some information leaked to the wrong party. And and at that point you fix it before making it accessible to all via agents. Yeah. I mean, that's what you say, right? That is the key point there. Uh it's then accessible to agents and they spread the information even further because you know, there is MCP, right? Uh so, you call all those tools that are registered. They could They others call your tools that you offer and then you have the agent-to-agent protocol, which means that the agents now talk to each other again as well, yeah? So, it is **[00:30:00]** crucial that the access to that information is validated first hand, yeah? Because it is then spread, yeah? And it the auditing is also important because uh uh believe me, what our customers often have is, "Why did we come to a certain decision?" Yeah? And then you need the process audited, yeah? It can't be that the answer then is, "You know, I asked the AI, I have no clue where the information comes from." Uh that's I think not the future we have to dream of or we should dream of. The future is more like, you know, I asked my assistant, my AI, my agent, yeah? They provided this information because of, yeah? And then there's the whole list of context and information and knowledge, the trusted knowledge, yeah? Uh that at the end of the day works out to a final decision, right? And I think that's that's what we aim at, right? Uh excellence, quality, yeah? And speed combined, and not pure speed and we and don't care about excellence and quality. I think that would be totally wrong. The more AI you have, the more important is quality and excellence. Mhm. Yes. Speed is a tricky tricky subject because you get used to the chat answering super fast, which is great for conversation. But I tell people, well, yes, but if you're asking it a deep question or something that requires getting data, and it takes a few seconds to give you that answer, that should be okay because it's even strange that it would give it to you so fast. Because if you would ask someone, even if they have the information right in front of them, or they're a subject matter expert, **[00:32:00]** it will, if they're professional, think about it a little bit, process it, and then give you an answer. It's not like I ask you and you just blurt out the response immediately. For If you're careful. So, so why expect it to always be fast even at actual interaction time? Absolutely. And you have to trust it, right? Why? Because you try to augment employees with skills that they didn't have before because it was subject matter expert's skills of others, right? And you try to scale those skills for the whole organization, which means that you have to 100% uh be able to rely on that uh uh uh agentic use cases and information, because otherwise it's worthless, right? Because if I ask my legal team, I am quite sure that they know what to do. If I ask the HR team with onboarding process, this I'm quite sure they exactly know what to do because they are experts. But now I have those assistants and agents supporting me, so I have to uh trust them as well. And I think trust here I really comes from quality and excellence uh because um uh uh if you if you fail in a decision or even have uh uh you put uh uh damage to your organization because of a wrong decision, right? A critical one, yeah? You don't want then end up to this was only based because the AI was hallucinating. Uh that would be crazy, right? Um and I think that is that is what we are we are on the way to that, right? As as a whole uh uh uh world and economy, right? Because people are starting now from all those pilots they did to kind of move over to **[00:34:00]** production. And I think that that is a important an important step, but also I would say a critical one. Why? Because in a pilot phase, you know, you always control the data. You control the use cases, yeah? Uh you will have everything under control. But let's be honest, large organizations and even smaller one, the enterprise information is typically more a messy kind of thing. There are duplicates, there are contradictions in documents, yeah? It might be that often information exists that is that you would assume it's trusted, it's just wrong, right? And then there is information that was not used but would have been right, right? So you have all those cases and I think that is more important to have filters that try to understand the information, find the accurate one, find the important one and feed the the next stage of tools with that context and information. That will be crucial, right? I think that the the important step is coming from hundreds of pilots and hundreds of agents you are playing around with right now to real world use cases that you can fully trust. And would you suggest that when people are doing those pilots in their organizations and they're trying to test things out, perhaps start with something in the real world with real data, but that perhaps the risk of it going bad has a lower effect on the general company if something goes wrong versus having it go directly into high stakes **[00:36:00]** decision-making. I would I would always encourage customers to start with uh real world data with real world critical business processes. Why with the critical ones? At the end of the day you need an ROI calculation, right? At some point in time your CFO will show up and say, "Hey, we are doing this. This is quite a substantial amount of money we invest there. Is it a good investment? And then you better are able to make the business case because otherwise, right, it's a playground that nobody is interested in. At the end of the day, companies want to scale, companies want to be more profitable, companies want to kind of be more competitive. Yeah? So, the business case needs to to pay off. And I would that's the reason why I would start with first real-world data, real-world subject matter expert users and teams, yeah, and not only to an IT-centric evaluation. I would really evaluate it with the subject matter experts in the organization, yeah, and I would start first with some of your most critical business processes. Why? Because there are you have the real-world impact, right? And there are where you need that This is where you need the transformation very important. You you just That's That's That's the That's the most important, I would say, prioritation for an organization. And and you'll pay attention because it's great. 100% and your subject matter experts will try to show that the tool is nice, but they still are way better in what they are doing, yeah, which they are, right? Because I think it is not You shouldn't And I think that's the misconception of we hear always people are laid off because **[00:38:00]** people automated everything with AI, right? And I think it's AI-washing in many cases, yeah. It's AI-washing because at the end of the day, I think your subject matter experts are the strength of your organization, and you will need those to build capable AI solutions. Because if you do not have the knowledge, your business knowledge, yeah, you can try to teach the AI everything you want, right? But at the end of the day, your company works because of the subject matter experts. And now, you help those subject matter experts to even scale better for the organization with all of the knowledge. And I think that's what we all should aim at, yeah? It it's not laying off people and replacing people and then telling the marketing story of AI washing, yeah? Uh I think that's wrong, right? I'm a big believer in uh it to make AI work for large organizations and enterprises in general, you need the subject matter experts to help and teach the AI uh uh how to do things properly and excellent, yeah? And then, this will help the subject matter experts to scale, right? And if your organization scales, you will not need less people. You will need more people, yeah? Because there is way more boosting growing, yeah, than laying off people because everything is automated. I don't believe in that story, honestly. Also not from a society perspective, yeah? Because we knew humans tend to to to to wanting to do something that is fun and and gives us I would not say not only hope, but gives us a reason, right? And gives us the perspective, yeah? I mean, I think it's it's knowledge workers that are successful, right? I I think uh **[00:40:00]** they are working because they love to work, yeah? Many are not working because they have to. Many people are just love what to do, right? A- And humans, I think, need to do need to do things, yeah, that they really believe in and and it gives sense, right? It's It gives all of us sense of what life should be, yeah? I I couldn't agree more. There is a lot to unpack in what you just said. First being that humans apart from just the knowledge they have, they have all the experience. And so that person, that subject matter expert in your organization, sure they know everything and they they can bring in a lot of that knowledge into the company, but there are still experiential things that they have that they cannot express, but that if you ask the question, they will have the answer because of the experience and how our mind works. And that is something very difficult to replicate in AI. So, yes, exactly what you said makes complete sense because then that person will have more time to provide extremely valuable work for the company and the low value items can be offloaded to the AI to help the rest of your They're not low value, it's just lower value in terms of what they can actually provide, right? And so, yeah, scalability is tremendous. And also, you touched on quality of life, what people like to do. Yes, I always say, "Hey, don't It's not taking jobs away. It's If I have a person that's copy being a pasting cells all day, I don't think they they love that job. I don't think that's rewarding for them. So, if I can help by making AI do the copy and paste so that that person can do something else with their mind **[00:42:00]** that they actually enjoy and that they give value, then I think that's better. And then, as you said, as a company gets more efficient, it can have more revenue, it's going to grow more, it has more profit. Absolutely. So, it's going to need more people Absolutely. to fulfill. Absolutely. And even if you automate them, right? Like hell, because that's at the end of the day what what will happen, right? That the automation piece gets more and more and more, but that makes you even more scalable, yeah? Even more scalable and I would say uh resilient. Resilient makes your business resilient, right? Because people get sick, right? Uh people want to want to have holidays, yeah? Uh of course they won't, right? Yeah? Totally natural. I mean, we are humans. But at the end of the day, if you have something that in the meanwhile takes care of standard tasks, yeah? That's outstanding for every organization. That that gives a totally different level of resilience to the whole organization. And I think that's the way to go. That's the way to go and I think Yeah, that that will also show the future that AI pieces, right? And tools like Mindbreeze, yeah? Working together with humans to even achieve more together. And I don't believe in the uh replacement story. Mhm. AI replacing employees. I I don't believe in that, right? Jobs will change, of course they will, right? Electricity changed how we do things, right? Uh steel production changed things how we do them. Uh uh uh trains changed how we do things. Of course, I mean, the whole world is an ongoing change, right? Ongoing change everywhere. And that's the great thing, right? Uh there are many people who love change. I I mean, everything we see now with the eyes fascinating. It's fascinating and it's right that it's we **[00:44:00]** are at the beginning, right? Mhm. And that's that's what we also hear always uh CEOs from some of the biggest tech companies say. It's the beginning and that even the data centers just start off because, you know, there will be many more. Potentially, we will have some in space in the future and things like that. Really cool, right? But let's focus on the way to that, right? Because that there is a lot of fun, I think, doing all those projects with people around you. Yeah? You don't want to be this entrepreneur that just has agents around them and just earn money. I mean, working with humans in a team, doing creative things together, right? Uh having newer ideas of potentially things you think never did this before, right? That's really why we are here, right? That's what at least people like myself me drives that, really. Yes. Yes. I completely agree. That's that's a Uh Uh Let me ask you a a This is a personal thought I have typically and and and I like to get your your feel for it. There's so many people that it's so fun to interact with, especially retired, older older people, men and women that have been experts in their space such a long time and then they they retire and and what are they doing, right? There's There's some some people say there's no opportunity for that, but in my mind, it's like what? There's this huge, amazing pool of people that can give us the expertise that we need because they already lived and have 50, 60 years of actual experience and and subject matter expertise that we should be pulling them back in, not to like work 9 to 5, but like to absorb some of that information and expertise and and put into systems like **[00:46:00]** Mindbreeze and and other enterprise systems so that we can use it to to increase our productivity, not make the same sort of mistakes, etc. So, what do you think in that sense? Do you think that's something Are there Are people Have you seen people actually doing that sort of movement or or do you think it's feasible? One of our employees, right? He worked up to 70, right? Because he just loved being in a in a in a software company, right? In an AI company, right? And I think it's not It's age is a number, right? Age is a number. It's It's the mindset. I mean, I would say there are people that retired and have a very young mindset, yeah? Because all of the change that happened over decades, yeah? They They kind of always tried to be on the very front of all that change, yeah? And I think that's the most important thing, right? And there are um There are millions of people like that out there, yeah? That just love to do things and love to work, and I don't mean hard work in the steel production, right? I mean creative work, trying to teach AI tools agents how to do certain things efficient and playing around with it, coaching other people with their experience, right? And I think um it was it was never as interesting, I would say, as today to do those things. I I really love to live in in the age we are living in, right? Because I can't imagine um I can't imagine a time frame in history, yeah? That was as funny to see the progress as we are doing right now. Maybe it was **[00:48:00]** with the Industrial Revolution, could be, right? Uh not sure because I of course didn't live in that time frame, but honestly, living in our current time is is a very It's There are things happening that are not great, right? But I think that are not topic of that podcast now. Uh but from a tech perspective and from an AI perspective, we live in extremely interesting times. Yes. Yes, you say funny and and it is. It's like a science fiction novel. It's uh everyday something new and radical is out there. it, right? Compare what Back to the Future told us in the '80s and then compare where we are with that. I'm still waiting for the hoverboard, honestly. Yeah. But the rest is almost there, right? Yeah. Yeah. Amazing. And even better, right? Even better. Yes. Yes, because it's not I mean, it's so fluid. The the devices and things that we have I mean, it's still I I'm I hats off to Isaac Asimov and and those science fiction writers in the '50s that got so many things right that we're starting to see now. I mean, maybe some of it is because of what they wrote, but still mind-blowing how that happened. I'm super excited about everything that's going on and And if you know, if if uh uh if it could happen that Michael J. Fox listens to that podcast, right? I would really love to meet him in person once, yeah. He was He was the hero of my youth, right? And I really If there's a chance in the future to meet him in person, I will be there, right? Yes. Oh, yeah. Yeah, as would I. As would I. Daniel, it has been a blast having you on the show. I learned so much and I'm sure our listeners learned so much as well. If people want to learn more about Mindbreeze, maybe they they **[00:50:00]** want to think about it for their particular enterprise, their business, where is a good place for them to learn more about how all this works? It's clearly our website, right? It's clearly our trainings and I'm I'm here as well, so you can give me or our team a call at any time, right? And and we will explain you in-depth how we would do things and and and we are hands-on company, so we typically do hands-on try and buy this we call them. We always try not to only talk about the tool, we always want to show off our product, yeah? Because we are proud of what we do and we want people to use what we have achieved over 21 years, right? And we have never been faster in innovating our product than these days, right? So there is more to come for sure. Well, and and I applaud you for it. I've talked to many people at service or or even SaaS as a customer, right? Throughout the years and a lot of it is like they hold they have this whole sales presentation and thing and it looks like magical, etc., but those people don't really know anything about the actual thing, they just know the sales and then you get to the implementation it's a completely other thing not like you're explaining now where it's it's very clear that you're very hands-on and and you're actually like hey, this is the actual thing for real which which is what I would hope for for My roots are in computer science. My roots are not in sales or marketing. I'm a computer scientist, yeah. I kind of started computer programming in the age of 10, which was back then, you know, nowadays you would say everybody is doing that at 10, right? Back then, when I was 10, which is yeah, still some years ago, right? I I I was one of a few doing that, right? And I really loved computer programming **[00:52:00]** and I today still love it, yeah. And yeah, that's why we are such a hands-on organization because I think all of us here at Mindbreeze, we think of in reality we want to help customers to achieve things, yeah? And not only show polished slides, right? That's not why we are here. We are here to really change how enterprises work to make this vision of this one intelligent enterprise work for every customer, yeah? Yeah, and that's why we are here, right? That's amazing. I will definitely look into Mindbreeze more. Um I love these tools that actually help organizations. Um There's There's all this talk of SaaS going away and software dying and things like that, whereas if you actually know what's going on, quite the contrary, it's it's just giving us more power to create better more more more personalized tooling in a faster way, which is which is incredible. But again, I don't want to take more of your time, Daniel. Thank you so much for coming on the show. Thanks a lot for inviting me. Yeah, thanks a lot for having me. Thank you. It's my pleasure and everyone who's listening, make sure to like and subscribe if you haven't so that you are aware whenever we release new episodes like this fabulous one with Daniel. And if you want to learn more about Mindbreeze, I'll set the website on the show notes as well. So, thanks everyone and we'll see you in the next one. Thank you. Bye-bye.