A (4:02)

Can you talk a little bit about what you think is AI hype and what's real when it comes to the business world?

B (4:10)

I think that there are a lot of like AI is a hot topic, right? And I think that a lot of people are over rotated the topic of like job replacements and because it's very emotional and very catchy set of topics where people will react, you cannot be like, you cannot ignore it and not engage into this conversation. And I think that it also plays into sometimes wrongful understanding of a potential impact that AI can bring to the table. So I think that if we just forget for a second about this kind of job pacalypse and replacements and just look at the practical sense, that's where the magic begins. So I would strongly encourage our audience and business leaders and technology leaders out there look at what can be achieved with AI now in regards to the current state of technology and where it can bring the biggest impact. And when we unpack it, we see couple of kind of core scenarios. The first type of a scenario is when we use AI as, let's call it an assistant. When I'm writing an email or I am working with a customer, I want AI to summarize all the history of this customer and give me an insight how to personalize my interaction or I don't have time to read through 100 pages of a document. I want it to be bubbled up and summarize what is the key points and key takeaways for me, those types of assistant use cases can be a very significant time saver. They can be a productivity booster. And I can tell a little bit about my experience. My now with the usage of AI in communication with customers and partners and just with my team, I'm saving a lot of time. It's just much easier to do that with AI than without AI when it comes to this assistant mode. But usually a lot of people mistakenly think that this is the only one application of AI in the real world. In reality it's not. There is another flavor of AI. It's usually called agentic AI, or we call it autonomous AI. The idea here is that you can delegate AI as significant, if not the entire workflow within your organization, that by default there are multiple workflows and tasks that AI can do better than human being and vice versa. There are lots of different things that we can do much better than any machine, any technology, any robot. And if you know the nature of the kind of AI, you understand it's not real intelligence. It has a lot of very interesting skills. But you cannot compare intelligence of AI with intelligence or human worker because by definition there's also two fundamentally different things. And the winners of the future are the ones who will understand how to combine both. So coming back to my point, the idea of autonomous agents is that you define use cases and areas within your business that you can delegate to AI that can go and execute a very significant workflows on its own. And usually those use cases are very niche, very specific and related to specific verticals. Because it's very difficult to do a strong agent that is very broad. It's much easier to do an agentic workload that's very specialized and has a lot of domain knowledge and, and it understands how to execute particular tasks. So moving ahead, I'll be sharing some examples. But in industries like financial services or manufacturing, or even public services, there are a lot of use cases where organizations just spend colossal amount of time, colossal amount of time that can be done so much more efficiently. And this will end up releasing much more time for building real trust, real relationships, much better way of communication with customer, partner and employee ecosystems.

C (8:19)

Yeah, that's really a good way to break it down. And the agentic AI stuff is particularly fascinating because it can make us so much more efficient and sort of able to get so many more things done. So all of us on this call are marketing people, right? So we've all worked in the marketing space, so we have the pleasure of knowing very well what a CRM is right. But one of the things we like to do on this show is break down especially any acronyms for the audience out there who maybe doesn't know what that is or why your approach is unique in using AI in this space is so interesting. Maybe just give a very, very high level. What is a CRM and what kind of work does it do for business?

B (9:01)

Yeah, CRM is an automation platform that allows you to really streamline your workflows related to core commercial functions, sales, marketing and customer service. So if you are like a sizable business, like small business, medium and of course enterprise, you need to organize your workflow, you need to organize your data, you need to make sure that you can keep track of all campaigns, all opportunities, all customer cases and also more importantly automate a lot of those steps to free up time for your go to market teams. Historically the promise of CRM was that it helps sales leaders, service leaders to be more productive. But also CRM earned a little bit of a negative connotation specifically within a lot of teams that were like focused on updating a lot of data in CRM and really using CRM as a tool where I need to keep my manager happy by entering data into the platform. And the way how creature reimagined this is that we allow business leaders to achieve two things. First, we allow to significantly reduce the kind of data entry element within interaction with the system and significantly increase values that the user is getting. So you look at the CRM system and the ones that guides you suggest you what is the next step you want to do suggests you like gives you an insights you haven't thought about those types of things. So how can we refactor this and focus on value to the end user? Because if you do so then the user will be so much more productive and the manager will be much happier. Right. So that's.

C (10:46)

And that's being driven by AI, right. And like that's okay. So it's. You're not only sort of, you're practicing what you preach, so to speak. Like the way you act, your tool is actually built is using that agentic workflow and all that too.

B (10:59)

Yes. I'll give you a couple of simple examples to understand. We now have all different calls within our Zoom calls or Microsoft Teams or in email. We have tons of information and all of this data is so useful. Instead of me having a call with a customer, coming back to my CRM and updating all my records about what's my probability, what's my next step, what have I heard from this customer. Let us take all of these transcripts and all emails, go through them, understand all the insights and highlights and update all the systems. But also show me as a salesperson or a service person, where do I have gaps. And also let AI suggest me based on the best experience this company already has. What will be the next best action to overcome an objection? How can we really make this customer more satisfied? And AI can enable us to do that. This is a very important element in the interaction that changes the perspective and turns the table per se in rest to understanding of the value of technology. But there is a second element here. It's a no code element and configurability. Because for mid size and larger customers specifically a lot of organizations have a lot of unique processes. Some of those process related to the industry. Like by default a distribution wholesale company will act very differently from a bank, right? And companies in different markets due to regulations and other specifics will act slightly different even if they represent the same business domain and the same business industry. But then also each organization develops their secret sauce, right? Like something you do uniquely, something that really kind of embeds what is it that they add as a value within the process. And CRM is a digital DNA of this company to some degree. So you need to replicate your process digitally and that's where no code comes to play. We allow organizations to configure their workflows and do that with a, with a business in mind and do that not through backlog of change requests. Where you need to go to 18 will take six months to change. A couple of fields we can empower people to come in like I am as a business leader can be driving to work today and coming up with a new idea. This is a new workflow or a new business models that we want to launch. My team can go and configure this using visual designers in our AI and natural language. And I can create those unique digital workflows using the snow code aspect. And those two things are allowing us to create first, a really super positive experience for the end user that becomes so much more productive, so much more efficient. And secondly, it allows me to really go deep in regards to customizing and embedding my secret sauce and industry requirements and other requirements to make sure that it's not a cookie cutter approach for every single customer. Because in that case very limited to out of the box functionality.

C (14:16)

That seems like, oh, sorry, go ahead Anna.

A (14:18)

It seems like part of your secret sauces that you've helped people adopt. Like you say you've got this internal respect for. I've heard you talk about citizen coding, and I know that that's a. It may be outdated now, but within an organization, understanding workflows and these are people that you've identified within the companies that you serve that assist with this process and adapting it. So it's not a cookie cutter product. I think that's another important element of what CREATIO is doing. You're essentially like the UN interpreter for bringing people into this new world. And you've been so successful because you're not forcing workflows on people. I've personally run sales teams where somebody worked in Salesforce and somebody has been around since, you know, radio was invented, and they're just adverse to anything. They don't even want to talk about CRM. So I think that's part of your success. Yeah. Is that you've identified key, key, key players and within an organization and been able to be very creative about that approach.

B (15:20)

Correct. I think there are a couple of elements. I think that AI is forcing a lot of people to reimagine what they expect from business technology. And CRM and work automation is not something that is kind of stand aside. And also based on a lot of different, I think, indicators, we can see that classical, large, traditional vendors, they're not really good with AI and ability to bring it very quickly to solutions. And the reason for that is because a lot of them have grown through acquisitions, created very difficult technological stacks. And now organizations that experience ChatGPT type of productivity, they expect the same from business applications. Right. So they expect that my interaction with my business system will be very similar to my interaction with ChatGPT. Why it shouldn't be the same experience. Right. Can I, can I talk to my CRM instead of just, you know, going through this, hundreds and hundreds of different fields, updating this, and if I haven't updated this field, I cannot move forward. So this is nonsense for 2025. So I think that this is driving a lot of change. And secondly, I think a lot of people want to be empowered and nowadays we see that technology is becoming a skill. Like way before, I think when I was a kid, it was like 30 years ago, 35 years ago, my father was taking pictures of me and he was using this big equipment. He had this kind of big camera. And then he, he needed to hide in a big dark room to produce some of those pictures. And now like a 5 years old can produce better pictures than my dad used to produce using iPhone because we democratize access to this technology and empower people to, to do things without special skills and knowledge, et cetera. And the same applies to business people. So by default, business teams, they don't want to go through a rigid process of, you know, I need to explain what I want and I need to go through reviews and I need to wait and I get stuff that is delivered to me and it still doesn't fit exactly what I wanted. Instead, I want to be empowered to come in and say, you know what, let me explain to the system exactly what I want and let me go and iterate with AI as I'm developing a dashboard for myself or developing a new workflow for myself and kind of disregard those redundant and unnecessary steps. It doesn't mean that it doesn't have a say in this. But their role will become fundamentally different as someone who will steward, coach, organize, orchestrate, but not necessarily deliver every single small thing to a person. Which again, to my analogy with taking pictures, we do have more professional photographers now than we used to have, even though the skill became less expensive. And it's easier to get a skill and make, make pictures. But in a bold world, there is a place for everyone. But the function itself will be reimagined, in my opinion.

C (18:35)

And it allows like deeper. So when you think about instead of spending a lot of time on the data entry, which I don't think I've ever heard anyone say, gee, I wish I had could do more data entry. Like it's, nobody wants to do the data entry. Right, sorry data entry people. But like it allows you get to the insights much faster. Right. So instead of spending your time and I think about like in the medical field too, like we talk about that a lot. So yeah, that just seems like we're going to get deeper knowledge.

B (19:00)

Yeah, absolutely, absolutely. And I will give a couple of industry examples like, and I will come back to my message about two flavors of AIs and ability to apply them in the right example. So let's take banks or credit unions, right? So it's a big field, is a big economy. All of us in one way or another interact with our bank. So a good example with AI assistance will be, for example, I'm coming to my bank, but I have been a customer of this bank for years, years and years, and we work with one of wonderful credit unions in Indiana and they told us an interesting story. They were showing us member records that are 20 years old. So they have notes about a member of their credit union that are 20 years old. Just colossal amount of data Good for them that everything is documented. But imagine you're meeting this customer tomorrow, like how are you going to kind of prepare and understand how to personalize it to some extent, you know too much, you know too much about this member. So we're using AI there just to, you know, take the most important information, also check it on based on the history and time. What was probably super relevant 10 years ago is not relevant anymore. So how can we really surface an insight and enable a relationship manager at a branch with a very like, with very small synopsis of the data, but will be, that will be extremely impactful and that's where they see a tremendous potential. Right. So you get this information and members are happy because they feel like their credit union knows about them and it's very relevant. But also it empowers relationship managers to have much more productive and relevant conversations and also revert back to some of the conversations that happened before. So that's a great example of assistance. And then. But there are also some workflows that are ideal for agentic automation. I remember my personal experience going through mortgage approval and also mortgage underwriting. Oh my God, that was very painful. And every time, every time I talk about this with my customers in Belgium space, they all kind of give me the same facial expression. Like if we can avoid it, would like to avoid it. But now can really go and simplify and streamline this process like we can. We already have AI agents in Croatia that will go to a customer and they will say, you know, based on your type of a loan, it's going to be a commercial loan, it can be a mortgage, it can be a consumer loan. I need those five documents or 10 documents from you. And then AI can interact with the customer, read through all of those documents, make it very personal and relevant. So you're not dealing with five, seven different people who, with whom you just share this document. They forgot, they haven't like, you know, it's just, you're avoiding all this back and forth. So it's much better, quicker experience for the customer. And also we can use AI to go and scan all of those documents. Then for underwriting, prepare a pre decision and say those are five or ten documents that we have collected. We have done it through AI and we think that they're all legit and valid. But you take your call. I think there's a great example where a bank or credit union can be so much more efficient in regards to how they interact within this process. They're given a much better experience to customer and Everyone wins because they also can streamline this workflow and instead of a couple of weeks going through this process, they can potentially do that in a couple of days. And also AI can take some time and educate a customer where to get this document. Because for me some of the issues was just as a person who relocated to the US and to Boston specifically, like I was not aware of some documents, I never dealt with them before. So for me it also like I was a strange customer to some degree because I needed to ask a lot of different questions and some of the, some of, some of those questions were a little bit weird to someone who has been here for a while. So there are a lot of examples of that nature and AI can handle them much better.

A (23:18)

So it's really interesting that you bring up these examples. I've worked in banking and I've also worked in law. Kara is an AI founder in legal justice. And I find that, that psychology so interesting because I can tell you, even working as a bank teller, it is a very highly emotional situation where people, they want the personal touch and yet there's a lot of privacy issue there. So I think it's so interesting that you've struck this balance between creating a better experience, helping members of credit unions feel valued, which is why, let's face it, why people join credit unions, they want to feel like somebody knows them. But you've made this distinction between what AI can handle sort of on an impersonal and very speedy and get them through that process. It's very invasive to apply for, for a mortgage loan. And this is really interesting territory and really points out again what Creatio is so good at.

B (24:11)

Yeah, it is. And that's exactly why we take certain industries and we go very deep with those industries and we set up specific custom agents that are going like that are being predefined and ready to use for specific verticals because they can deliver a much stronger value. Because the values that you can get with agentic AI is very strong, but it needs to be fine tuned, trained, educated along the way. And it's also a lot of that is about partnership with customers. I think that part of this journey is that you cannot deploy it as we used to deploy, say cloud software. Here's your product. Go and execute your workflow. I think that the fundamental nature of AI is different. First we need to rethink the process itself. We need to understand if right now my AI agent is doing all this work. This means that my process will be changed. And like we need to realize this, it's not just me deploying a workflow. It's me deploying a new workflow and reimagining it at the same time. Like simple questions. If I have all those agents going and doing all of those use cases for me at the bank, how and who will be monitoring them? Like, what will be an interface of a person who manages agents? Those are new processes that bank or manufacturing company needs to establish. Otherwise, you cannot have it in isolation. Because AI will also, from time to time, hopefully not a lot, but will make some minor mistakes. But you need someone to address it, to act on this, to troubleshoot it, and then also use it to make it better for the future use. So that's a great example of, like, real partnerships that needs to happen between a provider of this solution and the service and the customer. And the way how we work now with a lot of businesses is that we tend to create very strong partnerships and very strong alignments. And we deploy our teams alongside our implementation partners into the customer side. We sit down together, we look at processes, we think about how exactly it will be working for this particular organization, because otherwise it just won't fly. It won't fly further than a pilot. And that's why you probably have seen some of those studies where people say a lot of AI deployments fail. And that's the reason why. Because if you want it to be really impactful, you cannot treat it as just a deployment of a software. Because if you want to make a significant transformation outcome, you need. You need to make this an organizational change process.

C (27:06)

Right. And for those people, it is. Yeah, sorry, we can cut that. For the people who are listening and not watching this, you won't know, but Andy has a very nice view over his shoulders there of the harbor. So that makes me Boston Harbor. It makes me want to ask a Boston question, if that's okay. You know, you're building. You're building in Boston, right? And you're building a unicorn in Boston. And I'd love to hear, we'd love to hear what you think about that ecosystem here and how it's. How it's maybe contributed to the growth of your company.

B (27:43)

Yeah. Car. A very simple answer. Boston is the best city in the world. And I truly.

C (27:48)

There you go.

B (27:49)

Yeah. Actually, I remember when, when I came here 10 years ago and I told my wife, she asked me, like, well, why we are relocating to Boston. I told her, it's the best city in the world. And she was, no, come on. Like. But, but, but now she kind of agrees with me. So I keep coming back when. When we fight, I keep coming back to this example you. I told you it's true and you know it's true. So I have joking because we never fight. So in regards to. In regards to the city, I think that there are multiple tremendous benefits to to Boston. It's incredible tech ecosystem. We have access to the best talent. It also allows you to see those best companies working together. It's also a very welcoming environment to if you want to build a business, you know you have a lot of support. We work a lot with State of Massachusetts Department of Economic Development. So we're in touch. We also city of Boston, like the city itself is our customer. We deploy some agentic use cases together. So this. The city is very near and dear to our heart and we have a lot of support and a lot of help. And also the kind of state market itself is just a big economy. Like if you look at gdp, number of companies, number of organizations. We love being here and we also love taking advantage that you know, we are local, we have headquarters in downtown and a lot of local businesses, they come to us because they want to work with someone who understands their their business.

C (29:21)

That's great.

A (29:23)

I'm curious just off the cuff, how many of your. I know you manage a team and this is maybe old intel, but I know you, I've heard that you manage about a hundred different people in your team. How many of them are AI agents or agentic?

B (29:36)

We have a lot of agents. You know, the overall philosophy answers we have is that we are obsessed with using our technology. Like obsessed. So that's kind of first thing that comes to mind. And the reason being is that if you don't see it at your workplace, it's very difficult to be passionate about this in front of a customer. Right. So we just got to feel it and experiences to go and evangelize it further. So that's why we look at Creatio's own system as kind of state of the art. The best possible solution that we want to have. This comes from multiple elements. We are trying to identify as many useful use cases possible and also we identify use cases in both categories. To give you an example of agentic category, we recently moved we have multiple tiers of support. Customers come to us with some questions, sometimes issues and we need to address it. We have three tiers of support basic and it works with the simplest questions and we have few level levels that are above that. So we were able to do our standard basic support also AI So we do have just a few people that oversee those responses. But now we even renamed our support to AI support, from basic package to AI support because 99% of all of that is managed by AI agents in creation. So we see the lockdown, we understand the responses, we understand the issues and also we keep fine tuning and adjusting the AI to make it more precise every single time. That actually allowed us to take a team that has been working on this and allocate them to higher tiers and more complex cases so that our customers are getting more white glove service, more attention and more human touch. So that was an extremely cool example of how we work it, how we work with that or another example that we love it's publicly facing. So we use an AI agent in our academy. So we create a lot of academy materials because we are very fast growing company. We also sell through partners and we have 700 partners across the globe and they have. So we need to educate thousands of people and every time when we release something, we just need to constantly invest into academy and materials. So we right now we use AI to produce all of our classes and we probably quadruple the productivity of all the materials we produce. But also we constantly were getting feedback that your platform guys is so much comprehensive that like when I want to go to your doc, your documentation and understand that small thing, it was difficult to understand where to find find it. So we deployed an AI on our academy and now you don't need to do that. So you are coming to a chat and you say I have a question about this particular issue and it will kind of surfaces user information, provides you with a link and actually we get 95% of satisfaction. So we are resolving like 95 out of 100 questions from the first response and our customers and partners are happy with that and we continue to fine tune it, enhance it and that provides another great experience for, for our customer partner communities.

A (33:03)

Well, congratulations. I mean I feel like we want to follow your success and follow the trajectory. I mean I love your attitude that you're a unicorn and that's where you're starting. This bodes well for the rest of the world. We like to say we're proud to represent a Boston state of mind to the rest of the world. You're certainly a world player and you know, congratulations on making Boston your home. I'm glad that you can represent and I look forward to a part two. This is just the beginning of my curiosity with what creatio can do. We certainly appreciate you adding to the positivity and the solutions in the world. So, Andy, please come back. And Cara, let's drop in and just see what we can do with AI we always talk about what can Building AI Boston do with AI in the future. So maybe there's a collab work. Sandy.

C (33:48)

Oh, I love that.

B (33:50)

Let's do it. So we are again, we're so super positive. And you know, it's. Boston is not a city where we operate and headquartered is very near and dear to our heart. And we also love building community around ourselves. We also have like a big AI event every single year in Boston. It's usually in full, so it's called agentic leadership. No codes in Boston. We this year we did it in four seasons overlooking a beautiful park. So we will announce the new date very soon. So. But we would be happy to see you, but also the audience at this event.

A (34:28)

Wow. We put that on the books, right, Cara? I mean, any.

C (34:31)

I know. I'm like, looking at my calendar. Write it down.

B (34:33)

Yeah.

C (34:34)

And outside.

A (34:35)

And yeah, like, love the positivity, friend. So thanks for spending some time with us. We look forward to that. And for our listeners, we will absolutely post in our community. It's a pleasure to. To meet such an astounding person as you and congratulations and wishing you lots and lots of success. It means good things for the world. Thank you for. Appreciate it.

B (34:56)

Thank you.

C (34:57)

Thanks, Andy.

A (34:58)

Thank you for joining us on Building AI Boston. Stay tuned for more enlightening episodes that put you at the forefront of the conversations shaping our future.