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Join us weekly to discuss the latest and greatest in low-code and digital process automation with executives and experts. Real conversations, no marketing BS. Hosted by Rob Koplowitz, John Rymer, and Ryan Duguid. Visit analysis.tech to get in touch about your personal low-code journey and learn about ways we can help.
Rob Koplowitz (00:08)
everybody and welcome to the latest episode of Lowdown on Lowcode. We're somewhere into the 20s. I'm not sure exactly which episode number we're on, but we've been kind of at this for a while now. I'm Rob Koplowitz. I'm one of your hosts today. My history is in enterprise software. I go back to low code development with Lotus Notes and worked at Oracle and IBM and Microsoft and 15 years at, at Forrester.
where I cover digital process automation and I collaborated very closely on low code research with a fellow by the name of John Rymer. How are you, John?
John Rymer (00:49)
Very well, Rob, great to be here. So I worked as an analyst for 25 years before taking a retirement vacation, I guess, for three years. Now back into it. And as an analyst, I always was focused on platforms to build applications, integration, developers, and developer persona, and so forth.
and stumbled on this emerging category in 2014 with my friend and colleague, Clay Richardson. We called it low code and the rest, as they say, is history.
Rob Koplowitz (01:32)
Thanks, John. So very quickly, our producer Jake and I spent some time with a podcast consulting company yesterday by the name of Wild Poppy Creative Consulting. Emily Holland and Angie Marie gave us all kinds of great advice and apparently we're supposed to be promoting ourselves. Who knew? I mean, I guess this is all new to me. So if you're listening, whatever format you're listening on, Apple or
Spotify or YouTube, please hit the like button, please hit the follow button. This allows other like -minded folks to find us in the future. So shameless self -promotion there. And now let's actually jump into what we're here to talk about today. So one of my favorites today, the CEO and founder of Bizagi and we go back a long way and we've been waiting for a long time to have him on and
We're so delighted to have you on Gustavo. Welcome to Lowdown on Locode.
Gustavo Ignacio Gomez (02:36)
Thank you very much Rob. Thank you for having me here. Please don't mention the number of years we have known each other for, okay?
Rob Koplowitz (02:44)
It's, it's got to be what 15 or something like that. it's, it's a while and it hasn't always, and then we've certainly had our moments where we didn't agree on everything. Gustavo, we like to start each of these podcasts with what we call the Trask moment. And we'll explain that at some point while we call it that, but it's, it's how did you get to be here? Why is our audience so interested in your story? How did you come to.
Gustavo Ignacio Gomez (02:49)
Yeah.
you
Rob Koplowitz (03:13)
Number one, just find your way into this technology industry. And number two, after that, what brought about your decision to found Bizagi Let our audience know just what an amazing story this is.
Gustavo Ignacio Gomez (03:28)
Yeah. Okay. Yeah. We started the company a long time ago in 1989 and the company started developing ERPs for Apple computers at the time. Yeah. In Colombia I'm originally from Colombia. So Apple wanted to develop an ERP in Colombia and we were students at uni, fascinated by the Mac and then they hired us to develop the ERP.
We then moved on to develop ERPs on the Windows platform. In those days, jobs have been sucked, Apple was going down, Microsoft was going up. So we decided to create an ERP based on client server technologies, Windows NT in the early 90s.
We later on sold that part of the business and started developing workflow solutions. As you mentioned, Rob, we started developing workflow solutions based on Lotus Notes, Microsoft Exchange in the late 90s. Basically, the situation we would always face there,
was that we would acquire a new customer to develop a workflow solution. And then we would go away for six months to code the workflow.
And after six, eight months, we would come with the final application, and the customers would say, thank you very much. But in the meantime, when you were coding, the processes have changed. We have new people. We have new regulation. Can you please adopt the solution? And we would say, yeah, of course. It will take us another eight months, and we will charge you another $100 ,000.
And the customer always asked, why is it so difficult to adapt software? Why do we end up adapting the business model to the software and not all the way around? So after listening to this from the customers again and again, one good day, we sat down with the engineers. And we thought, well, if we adopt model -driven technologies, renamed as low code.
And we create a clear process layer. We have the adaptability that our customers are asking for. Bear in mind that by then we had already developed two or three complete ERPs. And one thing that was obvious from the ERPs is that configuring the ERP for the specific needs of the customer was always really difficult. You had thousands of variables to configure the ERP.
And it became obvious to us that what you were trying to do with those variables was to create a process description specific to the customer. So this combination of the feedback from the customers plus the ERP experience, we said this is a cool idea. It provides the customers with a lot of flexibility and speed to deliver results.
And that's when we created Bizagi We're talking about the year 2003, so over 21 years ago.
Rob Koplowitz (06:43)
and Bizagi the name comes from.
Gustavo Ignacio Gomez (06:47)
It stands for business agility.
Rob Koplowitz (06:51)
That's good.
Gustavo Ignacio Gomez (06:53)
And we thought it was a great name. We thought this is a fantastic name for everybody that speaks English will immediately recognize what the name stands for only to find out later that nobody had the clue what we would be saying. So obviously this story has been started by engineers and not by marketeers.
Rob Koplowitz (07:07)
You
That's great, John.
John Rymer (07:17)
I didn't know that, Gustavo, that's a great story. Yeah, I think you were probably ahead of your time in prioritizing business agility in software. So, Bizagi been around for a good long while, very robust platform, lots of features, et cetera, obviously to focus on process. When your sales reps, when you...
Pick us, you know, think of a sales rep going into an opportunity. When that, when that sales rep hears the, the, the client talking about their situation, what are the characteristics that say to that sales rep? This is perfect for us. This is perfect fit for, for what we can deliver with our platform.
Gustavo Ignacio Gomez (08:09)
Yeah. The first thing is when we see the customer being conscious that they're embarking on a transformational journey, not on a specific process. And that's it, not on a transaction. We believe that what we do can deliver enormous value.
Rob Koplowitz (08:22)
Hmm.
Gustavo Ignacio Gomez (08:33)
But in order to deliver that value, you need to have the capability and the intent to deploy this platform across many, many processes. Then you see incredible results.
So we want the initiative to be business driven, not IT driven, and understanding the transformation and nature of deploying these automation capabilities across the enterprise. That's really important for us. Clearly, you must work together with IT. So.
We always like customers that see this combination of business and IT nowadays called Fusion Teams. But we identify that as a key aspect that is really relevant. And they must have the desire to industrialize this, to create a center of excellence of automation. That must be the end goal. And we created a framework to take them there by working together.
This concept of a long partnership and journey is fundamental in understanding the transformation and the nature and being able to connect the dots between operational efficiency and business impact and new operating models. That's really important.
John Rymer (09:57)
So transformation is I was going to drill it, ask you to drill a little bit on that word transformation, but I think it just did because it's a it's a very overused word, but it sounds like it is a productive change to the business, including new business models. You're not just paving the cow path of the processes you already run, you know, with by automating them, you're thinking about new ways of doing business. Is that is that the idea?
Gustavo Ignacio Gomez (10:26)
Yep, it's a journey. At the beginning, people don't really understand how these projects actually work because they go across divisions. There are politics involved. The platform, the low code platform, nowadays they are much better understood. But at the beginning, they went, people, customers would go like, what? You don't program? You don't code? You save the model, interpret the model in real time? What do you mean?
But then when they see the agility behind the platform, the capability to change things, then they get excited about thinking on how to change the business model to make it much more efficient. Normally, what we have seen in our customer base is that first they start digitizing the process. They don't necessarily think of full transformation.
But after that, after digitizing the processes and gaining all the efficiencies, they start thinking in much more ambitious terms. I would say in two strands, changing the operating model to try to make things much more straight through processing, better customer service, and
they do that by automating the activities. They start looking at the activities of the process and say, each activity, does it still add value? Maybe the activity was there because an old regulation that is no longer valid. And if it still adds value, and the value of the animations are several in what we do, then they look into automating.
Can we replace this decision making by an algorithm? Can we nowadays include the bot? And nowadays, can we be supporting that decision with AI, which I'm happy to get into later on during today's call.
John Rymer (12:29)
Thank you, Rob.
Rob Koplowitz (12:31)
So Gustavo I want to roll back the clock a little bit. I want to pull a bunch of strings together and talk about sort of the technology foundation that we're going to need to do this, right? So first off, John and I, we pulled our research together because we said ultimately digital process automation and low code are going to be the same thing. To build all of the applications you need, some of them are going, many of them are going to need
process, many of them are going to need modeling, modeling, in order to really transform, we're going to have to engage the organization. And that's going to start to get into these low code conversations. And at one point I had this concept of DPA wide and DPA deep, which resonated very well. And I'm thinking about you and I sitting in a conference room in Miami and trying to decide whether Bizagi was wide Bizagi deep. And you said...
Do you remember?
Gustavo Ignacio Gomez (13:33)
Maybe I was drinking a beer and you were drinking a coffee rope. Yes.
Rob Koplowitz (13:37)
You said we are the widest of the deep. And, and, and I'm pretty sure you were drinking a beer, but, but that really resonated. I think all this stuff is becoming the same thing. Right? So I think when we think about transformation, there is modeling. You have to be able to put this into a visual metaphor that the business can understand. There is orchestration, which the model will drive. It'll consume heterogeneous technologies. There is this concept of.
John Rymer (13:37)
You
Gustavo Ignacio Gomez (13:46)
Ha ha.
Rob Koplowitz (14:05)
Involving the business, which gets us into concepts of low code. Are we finally getting there? Gustavo are people now thinking about this in, this is a strategic investment that is going to be a backbone for transformation for broad scale optimization. However, we want to couch the benefits.
Gustavo Ignacio Gomez (14:09)
Mm.
definitely. I do think so. It has taken a long time, bro. But we're definitely getting there. I think the... Yeah, much longer. I think...
Rob Koplowitz (14:36)
Longer than we thought, by the way, Gustavo, which is one of the reasons that John and I are less retired than we used to because we were so frustrated with how long it's taking. But yes, but sorry to interrupt.
Gustavo Ignacio Gomez (14:46)
Yeah, yeah. It has been a journey. I always found the journey fascinating in our industry. And when the RPA hype came about, I was kind of jealous. I was like, why is there so much excitement with these bots? They fitted perfectly into our model. We saw them as a way to automate activities, as I just mentioned. Another.
and other technology to orchestrate and make the process more efficient. So we welcome the bots very much. The level of excitement was what I was more jealous about. I was like, of course there's value there, but in the end to end process automation, there is much greater value. Now that I look back, actually, RPA has helped our industry a lot.
people really understand the difference between automating a task and being able to have visibility and trying to automate the end -to -end process. So I see a significant shift happening now towards our industry because the RPA helped mature the understanding from the customers. And in parallel,
We had all the cloud transition. And the cloud transition, at least in our case, we made the decision to be cloud only, not cloud first, and native to running the cloud. And the main reason behind it was to accelerate the innovation. The reality is when you're supporting all those on -premise versions of the software with different versions of the database and the operating system, you allocate a huge amount of resources just to keep the lights on. It's crazy.
So we made that decision a couple of years ago. It was a tough decision and we had to transition everything, the technology, the business model, which is consumption based in our case. We don't charge by name users. Yeah. Create the customer success capability, a huge amount of change in order to get there. But it's paying off for us fantastically. The level and the speed of innovation that we're delivering now is
It's fascinating and it's exciting. And this is coinciding with the interest and more and more focus in our industry. So I do believe it has taken longer, Rob, but we're getting there. Both the technology is becoming better and better. As I mentioned before, one of our first customers was Apple. So the concept of the application being intuitive has been in our DNA right from the beginning.
It couldn't be targeting just developers. They had to target these fusion teams. And we have seen the results in very large organizations. And those customers act as beacons of the impact that the technology can have. And that helps enormously.
Rob Koplowitz (17:52)
That's amazing. So listen, Wild Poppy, our consultants also told me midway through the podcast, I have to stop and have a commercial. So I didn't know this either. So, so Gustavo, you specifically mentioned the role of RPA. I want to call out that, you know, part of Analysis .tech we have, Francis Carden. Francis was the founder of, of OpenSpan, arguably the first RPA company.
Gustavo Ignacio Gomez (18:02)
Okay.
Rob Koplowitz (18:16)
They were acquired by Pega and Dave Marcus, also part of Analysis .Tech, spent many years with UiPath during their astronomical growth. And by the way, I think everything you said about the role of RPA, they would agree with wholeheartedly. But if you would like to engage further with Dave Marcus or Francis Carden or John Rymer or myself or our chief economist,
Andy Bartels or our expert on product management and product, and product development, Ryan Duguid please visit Analysis .tech. We do offer many services to both vendors and end users. So commercial over back to our normally back to our, our normal programming, John.
John Rymer (19:08)
Thanks, Rob. You mentioned AI, Gustavo, and obviously AI is disrupting a lot of thinking, if not technology and applications. How are you thinking, how at Bisagio are you thinking about AI? How are you going to employ AI within the product to achieve your mission?
Gustavo Ignacio Gomez (19:33)
Yeah, I will mention some things technological and then I will move to a more strategic level. The whole GenAI revolution, if you want to call it that way, came at a very good moment for us. As I mentioned before, we had already done the transition to be cloud native and our platform runs on top of Microsoft Azure.
And as there is this agreement between Microsoft and OpenAI, they deploy those OpenAI capabilities in the private Azure cloud. So we were able to very quickly leverage the GenAI capabilities in the private cloud. So we're never sending information to the public internet. It's staying in the private instance of the customer.
And we apply governance so that you cannot ask questions or get answers to questions that you're not allowed to get or see. Like, what's the salary of the CEO or that type of questions. So if you look back in November when it was in 2022, the whole hype came about. Microsoft deployed the capabilities on Azure in April, May last year.
And by October, we had delivered powerful capabilities within Bizagi That's the speed of innovation that you can see from cloud native solutions. And we were lucky that it was based on the Azure platform. The way we thought about this is, OK.
we saw that most of the industry was very focused on co -pilots. And there's clearly value there. But again, because we want our initiatives, even with InvisAid to be business -driven, we said, okay, yep, we can help the developers with co -pilots. But are there other value dimensions that could deliver greater value?
And we decided to focus more on the business user again. And we said, how do we deliver value for the business user? In an organization, you might have 100 developers, and you might have 10 ,000 business users. There is a factor of value there that we wanted to exploit. And we talked to many of our customers exactly on what to do there.
And we came with this concept called Ada. We call it Ada for Ada Lovelace, Rob, John, yeah. Which is in the runtime application, you have this conversational analytics with actionable results. So you literally ask in natural language to the system, any questions, show me the largest loans from yesterday in the branch in New York.
Rob Koplowitz (22:24)
Yeah, yeah.
Gustavo Ignacio Gomez (22:46)
And we use the GenAI capabilities to process that and bring back the information. And once you get the information, it's not just the reporting capability. We have the context of all the data elements so that we can display relevant actions then and there. So that's AIDA. It's in the runtime environment for all the people that build an app, a low -code app. Actually, no code in this case.
with Visagi, they get this capability out of the box. You might think what this means because internally, of course, we use Visagi and we create reports also based on Power BI and I have a lot of reports. And always when I look at the reports, I come with an idea, hey, I would like to see this new dimension in the report. Maybe there is a correlation between this and that to improve customer service.
And I go back to the engineers, that dimension is not in the report. Can you please include it in Power BI? And they go, yes. Two weeks later, I have it. It's prosthetic. Now you have the capability in natural language to query all the information that is in the system. And of course, we are applying security and governance to all of this. So that's the second angle. So you have the copilots. Then you have this end user business productivity.
And the third pillar for us is after releasing it, we said, how do we bring the power of Gen .ai into the process and into the apps? And we came up with this concept that we call agents.
So agents are very similar to RPA in the way you configure them within Bisagy in the sense that you just connect to the gene AI and then you generate an agent. I'll give you an example. This is a real example from a customer.
This is in financial services. And in this customer, all the salespeople or the commercial agents capture all the notes of the interactions with the customers, like what things make them happy, what are things that they should be improved. And those notes are stored into a database. Now, it's very difficult to get insights about those notes.
It's very difficult for an algorithm to run this unstructured data through this unstructured data and see what are the most common complaints. It's almost impossible to write an algorithm to do that. It's so difficult. It's so easy for GenAI.
So you can create an agent that looks specifically into design structured nodes and brings back a summary of the most common new service requests or complaints from the customers. That's a real example of an agent that we're deploying at the customer. So we're looking at these three pillars. Copilots, you have definitely value there, and we're embracing them. End user business productivity.
and then the agents to embed them and provide really groundbreaking new capabilities for the process participants and for the people that use the applications.
John Rymer (26:25)
fascinating. When you by the way, just to clarify, when you say co -pilot, I want to make sure that term gets used a lot. If you could just explain briefly.
Gustavo Ignacio Gomez (26:34)
Yeah, yeah, transport pilots are on the development side. Yeah, like, help me create this business rule. Help me suggest to me a claims process. Suggest to me a retail loan process. Help me create this form. Would you mind suggesting a data model for this type of process?
That's what we refer to as co -pilots. We see them more of the development design time. Ada is a runtime capability for conversational analytics with actionable insights. And then the agents, they live in between because you define them at the same time, but they provide very new information to the process participants or the people that are using the apps.
John Rymer (27:26)
Thank you. We're so the implications of this are massive. I mean, the the Gen AI technology, Gen AI technology, older forms of AI, more deterministic things are all are all relevant and fairly new in terms of being applied in the mainstream. We're we're what's your vision of this? Is it does it take a whole lot of people out of the?
out of the process, for example, or does it allow for automation that we don't even think about? We barely have to even design it and it just happens. Where what's the vision, Gustavo?
Gustavo Ignacio Gomez (27:56)
That's it. No.
Well, there are many patterns we're starting to identify which are very interesting. We don't think that processes are going to go away by any means of the imagination, at least not in the short, medium term. And the reason for that is that the process provides the governance. Our CTO.
gave an example, he asked, we were having a discussion and he said, would you allow an airport to be run by AI today? And the answer was, no, no, no, no. And we started asking, why not? Well, because they hallucinate, they make mistakes, they invent stuff.
John Rymer (28:47)
Yeah
Gustavo Ignacio Gomez (28:56)
And we believe that even though the reliability is increasing dramatically, there are certain processes where that error, any error, automatic error is not allowed. It's simply not allowed. You cannot say, no, the two planes crash because AI made the mistake. But I don't think as a society we will accept that. So what we are seeing is what we call the make -it -checker paradigm, where AI...
creates a summary of a legal case.
But then the subject matter expert takes the input and says, yeah, this is OK. Check it, and it becomes official. So is that symbiotic collaboration between AI and the human validation, the expert validation, or a doctor, the AI might scroll through many x -rays and say, in this x -ray, this looks different.
But it will be the doctor that makes the call and say, yes, that's a tumor, and we need to bring the person to surgery. So we see that symbiotic collaboration between AI and the human. It will make it hugely more productive. And the capabilities for automation around AI are
enormous and we're just starting to scratch the surface. Now moving forward, it was interesting internally that beside you we have the typical town hall with the whole organization and somebody asked, do you think that we will be able to create applications by talking to the computers? And I said yes, yep, definitely.
Particularly if the platform has this minority side, what we call a full grammar, yeah, personas, verbs, nouns. If you have a full grammar, then you can map everything from natural language into objects in the platform. And we are not far away of moving in that direction where you just talk.
in natural language, and everything that you say can be mapped into the platform and an application can be created. So I strongly believe we're going in that direction quickly. That's how we see the evolution. And then you have, as I mentioned before in the example from the customer, this incredible use of AI to empower decision making by humans.
new types of summaries, insights into information, unstructured information, automation capabilities. This is really reinventing the industry. That's the way we see it, and that's the way we embrace it.
John Rymer (31:59)
Yeah, thank you. That's brilliant. Let's shift gears a little bit, although I think you mentioned this a couple of times. first of all, Rob, do you have anything you want to add to the AI discussion?
Rob Koplowitz (32:11)
No, I kind of want to jump into the next topic, John. I'm excited to hear what Gustavo has to say.
John Rymer (32:15)
Okay, great. So you have talked about business involvement and how critical that is. Business -led engagements leading to long journeys, et cetera. There's a lot of what we're seeing out there is people struggling with how do you actually structure business involvement in the creation of these applications. You've mentioned Fusion teams.
which I think for clarity's sake is you're fusing IT pros and business experts on the same team and they have responsibility to deliver together, correct?
Gustavo Ignacio Gomez (33:01)
What you just said is very important, together. Yeah. No, it's not that this is a person in the business unit sending requirements. That doesn't work. You need that business people inside the team. And this is critical. Yeah. So going back to your question, there are many...
John Rymer (33:05)
together. That's right. It's not it's not the business person sitting in the background.
Yep. Yep.
Gustavo Ignacio Gomez (33:28)
Many relevant aspects of successful enterprise -wide deployments of these type of technologies, we believe. And we have been working. We have seen customers of us doing really amazing stuff. The ones with the best practices, they create these fusion teams. One customer of us has got a very small team, five people in the automation capability.
and their productivity is through the roof. And we spoke to them, and what they had created were two teams. One team that they call the continuous improvement team, and one team that was the automation, the development team. And they defined very clean roles, or what each person in the team should be doing.
For example, the continuous improvement team would prioritize the business requirements because they understand the business. So if you have limited resources, they would go, we need to do this first and then this second. They would explain those business requirements to the automation development team. They would test the delivery from the automation team.
So again, two teams, continuous improvement and automation in a single team, working together to deliver for the business with very cleanly defined roles. And their productivity was absurd. Within like two years, they digitized like 50 processes with those five people.
So those kind of practices we have captured and we, for us, it's very important to deliver that know -how to our customers. Because internally, we know that if the customers are successful at creating this capability, then the number of processes that get digitized and automated just goes through the roof. And this benefits us because we have a consumption -based model. We only make money when the
customer is actually benefiting from the use of the platform. So we share that know -how and best practices from our customers with our new customers. Now, when you said, so that's important. This combination of businesses and IT is critical. It's absolutely critical. I also believe that the process automation industry
focus perhaps naturally too much on the process participants. So we allocate the work to the people that actually do the work. But if you think of a support process, the support manager,
might not be performing almost any activity of the support process for that group of the support engineers. And we have been good for a long time at delivering the right information to the support engineers. However, the information requirements from the manager, who is a critical stakeholder, are very different from the process participant. And if you don't cater for that in your low code environment, then
there is a disengagement between the process automation and the business managers. In our case, that was the reason for us to introduce something that we call Bisaii Apps, because we recognize that the information requirements of business managers are very different from the process participants, and we wanted to enable that capability.
As soon as you have the business managers using the platform on a daily basis, the adoptions across the business change dramatically. So that's the way I see one of the hurdles that we were so focused on the process participants. And then the last one.
is to really understand the connection between operating models, operating efficiency, and customer service, profit and loss statements. You must see that connection clearly, and you must be able to present the business case behind this for people to go, OK, I don't understand the technology, but if you can deliver this business case, we go for it.
John Rymer (37:56)
Hmm.
Really great points. I thought one of the points you were going to make was that if we in the industry, in the process industry, have focused too much on the people who are operating the processes, there's a great risk that they will cause us to pave the cow path. And we won't get the outside thinking to say, how could the process be better that you get, you know, that you hope for? You just don't want to pave the cow path. Is that
Is that something you also have ideas about how to accomplish?
Gustavo Ignacio Gomez (38:40)
Yeah. No, well, I think it's connected to what I just said. It's like you need to cater for all the levels inside the organization for the process participants, but also for the business managers. And they need to see the value proposition there. And they need to be able to understand the system and interact with the system. The system cannot be a development environment because if you show
a screen full of code to a business person, they will say, thank you very much, but bye. You're not speaking my language. And then you must have the capabilities to connect your language to the business language and express and translate how these, for example, you are going to automate an activity. Why are you going to automate?
I'm going to reduce the service times in this much for the end customer. And we know that reducing the time provides a competitive advantage on the business because the shorter the time, the more business we get. Boom. Then people go, yes, now you're talking my language. You need to be able to use that language to the business and present it in a business case.
John Rymer (39:56)
One other, one last question for me anyway, about this in talking about AI, will citizens, will business people be involved or can they be involved in actually creating those agents you described? I mean, it's, it would seem that they know best how to apply this technology, but how do they get involved to actually create those things?
Gustavo Ignacio Gomez (40:22)
Well, I think the best way to answer that question is to explain how those agents work here at LeasingBesides. You write what in natural language what you want to get. I want to get the summary of the complaints from the customers that were in the example I gave in those docs. You write it in natural language. Then we have something that we call a prompt assistant.
It's
So you press the prompt assistant and that button creates a very Bisai specific prompt because it knows the data model within Bisai. So you don't need a prompt engineer next to you. It creates a Bisai specific prompt to be accurate that you can modify. Then you can test it and you'll see the result. The result in this case would be.
The most common request from our customers is to improve the response times. You get it in natural language. So these agents can be created by business people almost without any technical support. And yes, there is governance and security as in any enterprise application, but AI is empowering so many people that don't know coding or anything to go into actually do.
John Rymer (41:47)
Yeah, they don't know what a rag is and they don't know any of that stuff. That's that's a really crucial point. Gustavo, thanks for that. Rob, back over to you.
Rob Koplowitz (41:58)
Yeah, listen, guys, this has been great. Gustavo, I want to thank you for joining us today. Just fabulous insights. Love your perspective, your history, where you think this is going. Just thank you for taking the time to help us and our audience here today. yeah, no, we've got to go.
Gustavo Ignacio Gomez (42:17)
No, thank you. Thank you guys. It's always a pleasure to talk to you.
Rob Koplowitz (42:22)
always good. Always good to spend time with you, Gustavo. And, you know, for the audience, if you like the content that you're hearing today, please hit the like button, hit the follow button. And thank you everybody for joining and taking time out of your day to listen to our thoughts on Lowdown on Lowcode.
Gustavo Ignacio Gomez (42:44)
Thank you