The Complete Guide to Data Architecture for SMEs and AI Integration

📄 Management Summary

Data architecture is no longer a luxury reserved for large enterprises. With the rise of AI, real-time collaboration, and increasing system complexity, small and medium-sized enterprises (SMEs) must adopt modern data architecture practices to stay competitive. This post explores Codoflow's pragmatic, bottom-up approach to data modeling, emphasizing transparency, collaboration, and design-first principles. Perfect for startup founders, tech leaders, and IT managers looking to future-proof their data infrastructure. Learn more about our guest Stefan Opitz on his LinkedIn profile.

🏠 What Is Data Architecture for SMEs and Why Does It Matter?

Data architecture is the blueprint for managing data flow, integration, and governance across an organization.

Why does every company need it?

• Enables AI-readiness with trusted, high-quality data.

• Reduces operational risk and improves compliance.

• Facilitates faster integration of new systems.

🌟 Featured Snippet Optimized Answer:

Data architecture is a structured framework that defines how data is collected, stored, integrated, and used within an organization. It ensures consistent data flow, quality, and accessibility for operations, analytics, and AI.

👨‍💼 Who Owns the Data? Why Responsibility Is Critical

In many SMEs, data ownership is ambiguous. Codoflow changes this by assigning ownership at the system and interface level.

People Also Ask:

Who should be responsible for data architecture in SMEs?

Ideally, each system and interface should have a designated owner who maintains its data model and integration.

What happens when no one owns the data?

Confusion, poor data quality, and integration failures. AI models trained on such data will be unreliable.

⚙️ Bottom-Up vs. Top-Down: Why Traditional Models Fail SMEs

Traditional top-down approaches are too slow and expensive. Codoflow's bottom-up approach starts with real data, allowing for:

• Faster implementation (within 12–24 weeks)

• Real-time integration mapping

• Transparent data lineage

How does Codoflow implement bottom-up modeling?

By extracting schema-level data directly from systems and assigning responsibility for each component.

Can SMEs afford this?

Yes. Codoflow was built specifically for SMEs, providing enterprise-grade functionality at an SME-friendly scale and cost.

🧠 AI-Readiness Begins With Quality Data

Before training an AI, you need trustworthy, transparent data. Codoflow ensures this by:

• Mapping every data source

• Creating a clear integration landscape

• Supporting version control and change management

Why is data transparency essential for AI?

You can’t train AI on unknown or inaccurate data. Codoflow lets you track every input back to its source.

🤝 Real-Time Collaboration: Stop Using Excel for Data Integration

10/10 integration projects begin in spreadsheets. Codoflow replaces them with a real-time, model-based web solution.

Key Features:

• Split-screen views: Data tables on one side, models on the other

• Miro-like collaboration: See team changes live

• Built-in permissions and versioning

How does real-time collaboration improve data architecture?

It accelerates decisions, reduces errors, and makes integration scalable across teams.

⚡Meet Codoflow

Codoflow is a German SaaS platform redefining data architecture for SMEs. With a bottom-up design-first approach, real-time collaboration, and built-in change management, Codoflow helps companies unlock AI-readiness and data transparency.

Learn more at: https://codoflow.io

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🔗 More Related Content

• Why Bottom-Up Data Modeling Beats Traditional Frameworks for SMEs http://startuprad.io/post/why-bottom-up-data-modeling-beats-traditional-frameworks-for-smes

• How Poor Data Quality Undermines AI Training and Business Intelligence http://startuprad.io/post/why-bottom-up-data-modeling-beats-traditional-frameworks-for-smes

• Real-Time Collaboration in Data Architecture: A New Standard for SMEs http://startuprad.io/post/real-time-collaboration-in-data-architecture-a-new-standard-for-smes

🔗 External Links

• Crunchbase: Codoflow

• Tech.eu Coverage on SME Data Trends

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Follow Joe on LinkedIn: Jörn Menninger

About the Author:

Jörn “Joe” Menninger is the founder and host of Startuprad.io — one of Europe’s top startup podcasts. Featured in Forbes, Tech.eu, and Geektime, Joe brings 15+ years in consulting and tech strategy.

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Automated Transcript

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:00:20]:

Hello and welcome everybody. This is Joe from Startup Rate Zero, your startup podcast and YouTube blog. From Germany today I would like to welcome Stefan Opitz here here, the founder and COO of the Code of Flow GmbH, which is a German form of Ltd, a groundbreaking SaaS platform that is transforming data architecture management. With a rich background in IT consultancy and a deep understanding of the challenges in data integration, Stefan recognized the limitations of traditional top down approaches to data modeling. This insight led to the creation of Codaflow which adopts a bottom up data data modeling strategy emphasizing granular data level design to automatically generate higher level architecture views. And this integrates automated system landscape generation, real time collaboration, integrated change management and design first approach. Join us as we delve into Stefan's journey exploring how Codaflow is enabling organizations to achieve the transparent, collaborative and governed data model design, ensuring seamless integration and minimizing data risks almost without mistake. Stefan, welcome from Munich.

Stefan Opitz | Founder and CEO Codoflow [00:01:40]:

Well, thank you for having me. And actually I guess we are done now. It's absolutely amazing.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:01:46]:

Yeah, we're done. Hey guys. Was the shortest recording ever. Goodbye.

Stefan Opitz | Founder and CEO Codoflow [00:01:49]:

Exactly. Glad being here.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:01:53]:

Most efficient introduction ever, Jack. Thank you to Shizmi, my virtual assistant who made this possible. Thank you. That said, let us talk a little bit about who you are and what you did and how you went from consulting to found a code of flow and then we may already hint to our audience that data Data architecture. Data architecture management is a pretty boring data, but it gets very, very important if you want to train an AI on your own data.

Stefan Opitz | Founder and CEO Codoflow [00:02:29]:

For instance. Exactly. Yeah. As, as you said. Actually I'm coming from a consulting background and I still run like a very specialized consulting company and background and fun fact is that we actually were looking for a solution first. So it's not like that that we came up with the idea, well, let's found coder flow and let's do something completely different. It was the other way around. So we were looking for solutions in a data architecture area because we were facing certain challenges over and over again because we're doing a lot of integration and we are chasing after data like all the, all the time.

Stefan Opitz | Founder and CEO Codoflow [00:03:08]:

And yeah, at some point, well, we simply said okay, if there's nothing out there which is really satisfying us and everything is usually targeting enterprise level. And we simply said okay, well let's then simply try to disrupt the world and let's make it a better place at least from the point of the data architecture.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:03:33]:

Make the world A better place. Okay. Yeah, That's a pretty high goal. Yeah.

Stefan Opitz | Founder and CEO Codoflow [00:03:37]:

Yeah, I know. Bold claim.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:03:40]:

Okay, great. You talked about you want to do that stuff yourself. Can you tell. Can you give us a little introduction, just a tiny bit on why data architecture is important for all the companies out there? Not the ones who are very tiny and running on one server, but the ones as soon as they start growing, especially growing very fast.

Stefan Opitz | Founder and CEO Codoflow [00:04:08]:

I would even go a little bit further than that, actually. I believe data architecture is important for everyone and it will become more important. But the main challenges we were actually facing is that whenever we came into a new client and we were asking for their, let's say, how is your setup running right now and how is your integration working from a technology point of view? They were actually rather like, that was rather a short discussion because then you just show a couple of slides and then that's it. But as soon you wanted to actually deep dive a little bit into the details of it, what information is being exchanged, where is that actually being forward audit to and all that, then it was becoming a completely different discussion because then people would not be able to answer that and would actually just send you somewhere like, just like, basically, well, go away and ask someone who knows. And then the next question was like, well, who knows? And, well, we don't know, but that person might know. And then they just like push you, like basically from door to door. And that is, I believe, one of the main challenge in general, that our IT world becomes more and more a network of different systems. I mean, there are studies out there, right, saying like, okay, well, in average it's 112 systems.

Stefan Opitz | Founder and CEO Codoflow [00:05:28]:

Others say, like, it's even 200 or even more. All of that information is being exchanged. And apparently to my, let's say, experience, I have never met a company who has full control on all that. And I think that is one of the, let's say, rather infamous elements of data architecture because it's always outdated and no one knows and is even identifying it. It feels like if you're comparing these foldable maps for streets to Google Maps, it's a little bit like the same way, if you're lucky, you have an outdated plan of the 1970s and you are trying to find your way.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:06:16]:

And personal experience is that in the IT of very large organizations, there are usually a handful of people who do have an idea of the general data flows around. But it starts to get really tricky if you dive into the details when you want to put something together like a data lake or something, where's the data coming from. From this system? No, it's coming from this system. No, it's coming for.

Stefan Opitz | Founder and CEO Codoflow [00:06:44]:

Exactly.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:06:44]:

Then it gets real, real tricky. When we discussed before you told me there's a bottom up approach. So what do you do? Do you give a vote to all the bits out there?

Stefan Opitz | Founder and CEO Codoflow [00:06:56]:

Something, something like that. So. Well, bottom up approach is. And I guess we need to put that a little bit into a perspective. Common frameworks, common methodologies usually break things down. So you start like from a very high level and then you're just like breaking it out into like smaller pieces. And that is something which absolutely makes sense in certain areas. And apparently it has been let's say the typical approach for data architecture as well.

Stefan Opitz | Founder and CEO Codoflow [00:07:31]:

Let's say that is part of the problem from my point of view because when we are talking about data, if you actually talk to a person like these experts you were just mentioning, if you have such an expert, they usually have a deep knowledge on a particular system, on a particular data structure. It's very rare you find someone who knows all the systems with all their data elements in there. It's like I have never met someone and I don't believe it is human, humanly possible even to get there.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:08:05]:

For everybody who's now out there smiling, you should once, at least once try to understand those massive databases who only are out there to grasp data flows. It turns your head upside down within a few days and after month you have not fully grasped it.

Stefan Opitz | Founder and CEO Codoflow [00:08:29]:

Absolutely. And that's exactly where we are coming from. If you think about this one expert, the expert knows exactly what the data structure looks like. And quite honestly data structure is compared to a business process which is likely. Well, which is important as well. But it's usually designed right, so it is something. Well, they're like BPMN 2.0 models and all that. When it comes to data, we actually can take the data from the data source.

Stefan Opitz | Founder and CEO Codoflow [00:09:01]:

It's actually available. It's not a design question at that point. It's actually just like taking the reality and mapping it into some sort of model. And if you're doing that, and if everyone would do that, then you are starting at the bottom. And if you are having now all the details from a technical point of view, it's rather simple than to aggregate the information. And let's say you have a System Cont containing 10 objects and each object has 10 attributes and that information is being shared with a different system and going to some other objects and attributes then you can simply well state, well, there is information flowing from system A to system B. It's something which is technically rather trivial to actually, well get as an output. And that's kind of like what we did.

Stefan Opitz | Founder and CEO Codoflow [00:09:53]:

We said, okay, make it simple. And if you start from the lowest level of detail, then you can aggregate the information, information to whatever you like. Right? But that is the magic behind the bottom up approach.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:10:08]:

So let's go a little bit into implementation and start to understand how this normally looks like. Because I would assume you need at least one point where you actually connect to the system and get some access to all the data flows and then you do an automated mapping. Is this something that happens? And how long does your whole process take?

Stefan Opitz | Founder and CEO Codoflow [00:10:36]:

Fair question. And quite honestly that is one of the most asked questions when we are, when we are talking to customers. Let's put it this way, we believe that a tool in itself is not worth anything, right? So you need to have the right methodology behind it, otherwise you are just about a fool with a tool, right? And to actually get to a proper information. So everyone has still this idea of, let's say I want to automatically fetch information and send it somewhere, which translates for me into oh well, I want to give up the responsibility for my data quality and push it to some sort of API, to some sort of like automatism. And that is something which is contradicting to actually managing something. So yes, there are possibilities to upload like information, like the data structure. In that sense we have focused actually a lot of our development just on that particular part. Nonetheless, it is part of the methodology to have someone who is actually responsible for the data architecture for one particular system and even interface, everyone should have actually a responsible person attached to it.

Stefan Opitz | Founder and CEO Codoflow [00:12:00]:

It sounds weird, I know, because it is kind of like, well, you would expect that to happen. But reality is out there. Let's say there is a system. Oh, we have just another one. Okay, you already have two, now you have three. Go. Right. So that's the sort of responsibility we see out there in the market.

Stefan Opitz | Founder and CEO Codoflow [00:12:22]:

Because quite honestly it is nearly impossible for a company of a certain, let's say mid size to have a dedicated person for each individual system. Nonetheless, we want to make it easy. So, and there are different ways on actually getting there. The simple path or the easy path is you just start with a couple of systems. You are just taking the information you know of and you are just like putting it in and you have a responsible person behind it. So the implementation journey for that company starts essentially with two workshops as easy as that. First one, we explain how it works. And the second one is we are discussing how the process, the change process actually works, because that is the most important part to keep the whole thing alive.

Stefan Opitz | Founder and CEO Codoflow [00:13:16]:

Otherwise you're just getting a snapshot. So it needs work, it needs, well, taking responsibilities up on your desk and actually managing it from that moment forward. But the gains you're potentially getting out of that are by far outweighing that.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:13:34]:

We may add a little bit about the data quality. Why this is important because you can not have any good decisions when without good data quality. For example, what comes to mind is, especially if you don't have like the real structure and real data properly maintained in your system, for example, you cannot have any financial derivatives based on that because there, there's like a big danger in that. And that basically works for a lot of other industries, a lot of other tools there as well, especially concerning pricing, especially concerning compliance and so on, so forth.

Stefan Opitz | Founder and CEO Codoflow [00:14:14]:

And even pointing out the first point, you mentioning, you mentioned in your introduction, everyone wants to use AI lately, right? That's like the, like what the big. Well, that's like the new black, right? And you cannot use AI if you have proper data because usually AI is well supposed to train on data. So if you are not aware on your data quality and you don't know where it's coming from, well, how do you expect your AI or how can you even trust your AI model or your data model, which is coming out of that? For me, there is a huge risk that, well, numbers are sort of like proving that it works. But do you know how long it will work? What if something changes? Like, what if you need to train it on a different parameter? Where's the parameter coming from? Right? Yeah, but getting back to the implementation journey, like I was just like focusing on the easy path, right? So like let's start. Start simple. Of course there's another way that you can actually go in and use some sort of consulting partner who is then dumping everything into, into the code of flow environment and background helping you, setting up every tiny little bit. But all the whole process is, or the tools we are providing it should not take longer than 12 and let's be generous, like 24 weeks, because otherwise the data is outdated again. That's like what the majority of frameworks are actually suffering from because they are starting.

Stefan Opitz | Founder and CEO Codoflow [00:15:59]:

And actually we spoke to customers who are starting with like traditional tools in the data architecture environment. They start looking at, documenting it and in the end it takes like two years and then they have a picture which is two years old. I mean, how Useful is that it's simply, well, not going to fly. That's very simple and we are trying to change that. So that's exactly where we are really putting a lot of effort in and to make it as easy and pragmatic and simple as possible to get to a starting point and from that starting point. And that is, well, allow me to just point that out. You are not trying to document anything. It is not supposed to be a documentation tool in that sense.

Stefan Opitz | Founder and CEO Codoflow [00:16:47]:

It's supposed to be a design tool. And I think that is like one of the major changes towards other methodologies because we believe that it should start inside of a design process and not ending in a documentation process. To actually gain control of it.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:17:07]:

You focus on a certain type called SMEs or in German Kam who's there? More than 3 million Smaller medium enterprises out there. I was wondering how do you cater to this, to the specific needs of this target group or why?

Stefan Opitz | Founder and CEO Codoflow [00:17:33]:

Why? Yeah, in general, data architecture in itself is usually part of something which is called enterprise architecture. It's a part of that and that part is let's say very complex and it is sort of, let's say only for the enterprise companies. But enterprise companies is well, maybe 25%. I don't know the exact number of the overall global industry but the challenges of having multiple systems and again the numbers of 100 plus systems is an average over all industries. So it's true for the mid sized companies as well. So it is actually a problem which is not reserved for enterprise companies. Actually everyone has the problem. So it was time to actually provide a solution for everyone as well and not only the enterprise companies.

Stefan Opitz | Founder and CEO Codoflow [00:18:32]:

So for that reason we were focusing on like okay, let's, let's do it in a pragmatic way. Let's really try to well tear down the boundary of well, you need to invest multiple millions to make it fly and wait for multiple years before you can actually start using it. So for that reason we, we really try to come up with a way of working which is doable or affordable in terms of effort for everyone and not just like companies who can create a different department. Just focusing on that particular element of the design process. Does that make sense?

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:19:13]:

It does. We've been already talking about change management because change management is very important, especially if you do have new systems. Because if you ever try to do, to remove one system, just unplug it and plug the other one in. That may work in a small network, but if you do have more than 20 employees, it will usually not work, or at least as well as one would like to have it. So we need to do some change management. And how does CudaFlow facilitate the effective change management within the IT systems?

Stefan Opitz | Founder and CEO Codoflow [00:19:52]:

Good. Very good question. Actually, I think that's like the biggest differentiator between our solution and, well, let's see other. Other approaches out there in the market. So here as well, pragmatism first, there is no need of a complex solution for a complex problem, right? So you need to come up with a simple way of solving something. And here is something, well, which we did not invent, but simply reused. Any software development company is so used to actually use code repositories. Essentially, data and its architecture in that sense is something like a code file.

Stefan Opitz | Founder and CEO Codoflow [00:20:36]:

Like, it is a structured way of describing how your data looks like and how it's actually built up inside of a model. So you can use that and use versioning behind that. So that's number one. So if you are doing versioning and you can ask anyone who has ever done some sort of, let's say multiple people trying to contribute to a software project, you want to have something, what is called a pull request, right? So you want to have someone being the quality gate or the gatekeeper for anything which is going to move into that code repository. So we simply reuse that. So whenever you are trying to come up with a new release, and the release for us means that you have changes inside of your data architecture, the system is going to follow up and trying to find out, like, okay, like, where is that data being integrated to? Where is it being shared? So who do we need to ask for approval if you may do that or not? That's like literally like what I have not seen in the market so far. Because this is really implying that you are asking up front before you're doing a change. And if you're thinking a little bit ahead of, you don't need to necessarily do that at the very end, what usually happens, like after testing, you can actually start asking that particular question in that tool, in the design phase, so you know actually what is coming up.

Stefan Opitz | Founder and CEO Codoflow [00:22:07]:

And you can inform the people who should actually react up on that. Right. If you're changing your field in a system, that might actually affect an interface and that interface might affect another system and so on and so on.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:22:22]:

And it might affect the process of how somebody does his or her work.

Stefan Opitz | Founder and CEO Codoflow [00:22:27]:

Correct? Correct. And that's like the beauty of it, because we would well suggest to start with that instead of waiting for everything to be done and then starting testing and like, oh, well, it fails. Why? Yeah, because there is not. Well, this field is now not supported anymore in our interface because there's a field length of 10 and we have now 12. I don't know. Right. Just coming up with something. But that's essentially now you can actually say, well, okay, I want to Change it to 12.

Stefan Opitz | Founder and CEO Codoflow [00:23:00]:

Who do I need to actually ask? And the system will figure out the path of that particular element throughout your whole data landscape and will create a task for everyone and asking the question, okay, well are you feeling okay with that change or do you need to react up on that? And then we are basically orchestrating that communication between the different system owners and sort of like pushing out the change before it actually happened.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:23:32]:

That sounds pretty interesting. We will be back with more stories about you and kodaflow after short ad break. Hey guys, welcome back to my interview with Stefan Opitz of codaflow. We will be now talking a little bit about real time collaboration. In what way does CodaFlow enable the real time collaboration among the stakeholders in the company?

Stefan Opitz | Founder and CEO Codoflow [00:24:06]:

That's actually a very, let's say, critical element of the whole solution. So again, coming back to our past, so we have been doing a lot of integration projects between different systems. I would say 10 out of 10 start with a sentence, let's open up an Excel spreadsheet and let's combine forces and mapping fields and objects. Well, in some cases might not be Excel, it might be Google spreadsheet. Doesn't matter. Right. But in the end it's just a spreadsheet where everyone is trying to collaborate on main drawback, you don't have any data model information at that point. You just see, well, attributes.

Stefan Opitz | Founder and CEO Codoflow [00:24:50]:

It doesn't tell you anything about cardinality or anything. The other point is I have seen it. Oh, let's filter it. Oh, let's resort it. Oh, unfortunately I did not had like all the different columns in my, in my, well, working area and suddenly the work is gone. Right. So has happened to me multiple times. So we said, okay, let's stop that.

Stefan Opitz | Founder and CEO Codoflow [00:25:15]:

Let's actually put some sort of model behind it. So meaning that we create purposely our solution as a web solution where everyone can collaborate in like, like in a Miro board, for instance. So whatever you're doing, the other person sees at that very moment. And we have a split screen approach, meaning that you can have on one hand your table with your attributes. On the other hand you can actually see the data model or even the integration in itself and you just like basically connect the dots as well. Working, talking to the other person who is responsible for the other part. So it's basically if you're part of the left side, you're connecting the middle part and the other part is connecting the middle part to their part. And this is like how we envisioned how we would like to work when we talk to someone, because usually we are in like the left part of that system.

Stefan Opitz | Founder and CEO Codoflow [00:26:12]:

We are providing information and we would like to simply say, okay, well what do you need? This is what we have see here, putting it in and saying, okay, let's now actually talk about like how this is actually being connected. So that's kind of like our approach. So we purposely didn't want to create another spreadsheet solution. We wanted to combine a system model including the, let's say Excel like experience and background, plus putting some permissions on top of that. Because we felt like that is something which is desperately needed in that regard.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:26:55]:

I have a question in terms of understanding, you do this once and the system then automatically updates itself.

Stefan Opitz | Founder and CEO Codoflow [00:27:04]:

It does not update itself in by definition. But remember I said we have the design first approach. So if we would actually go for the system to update it by itself, like using some APIs or reading SQL tables and background and all that, that would actually be really difficult to handle because we want to actually react before the change happens. So if we want to react upfront, then the approach is, well, we have to design first, meaning that you are planning what you want to do before it actually happened. So for that reason you are starting at that point. And the second part is you have a versioning model behind it. So if you are uploading something, well, to what version, to what release is it already approved? Do we merge? Who is deciding on that? Right, so these are all the little elements which are, let's say, well, the consequence of having a proper change management behind that. But it allows you to really have an unknown quality of your data model, which has never been done before because now you can actually trust the data, which is different from, from what we have seen so far.

Stefan Opitz | Founder and CEO Codoflow [00:28:16]:

No one trusts documentation except their own. Maybe.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:28:23]:

Really, maybe it does make sense. We've been talking about AI training. Data transparency is your big topic. How do you enhance this data transparency and governance? Because that is something you should first have nailed before you even start training in NIA or nail data.

Stefan Opitz | Founder and CEO Codoflow [00:28:44]:

That's excellent. Well, actually this is a perfect, well, next step because we were just talking about it. If we are talking about data transparency, it means to have a versioning behind it. It means that you need to have a trustworthy data source for that as well. Right now the majority of companies, at least I have seen, well, at best they have some sort of like, well, data dump called Confluence or alike. Well, no pun intended here. It's just that someone is writing that because it has been the contract that you are providing some sort of technical documentation. So you're just writing it down basically, well, dumping it somewhere.

Stefan Opitz | Founder and CEO Codoflow [00:29:32]:

And I would even say the majority of these documents is well read by yourself and potentially one or two other people. And now you have different systems and you have different contributors and everyone is writing it in a little bit different way. In the end you're getting, well, some sort of documentation, no arguing about that. But if you want to create a big picture out of that, it's rather impossible. And that's why we are saying, okay, let's bring everything in one spot and have a proper process behind it, have proper responsibilities behind it. And then suddenly you have a transparent data model and a data model which you actually can rely on, which you can trust on because you have put the proper processes in place to support that. But that only works if everyone is contributing, right? Otherwise you again will end up in a, in a well situation where you don't really trust the data anymore. And that's, that's the part.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:30:42]:

Could you talk about training AI? Could you also use your tool to investigate if something is going completely of the charts with the AI, if it's not inherent in the model itself?

Stefan Opitz | Founder and CEO Codoflow [00:30:56]:

Well, we don't touch the data in itself, so we don't know what the data is because we purposely designed our.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:31:02]:

I was referring that some AI models are known to go off the charts. They are unstable and some of them are performing good to really good. But they still can be, they still can be issues. And if you could use your tool to investigate if one of the issues may be in the data that you've.

Stefan Opitz | Founder and CEO Codoflow [00:31:23]:

Had to it, at least we can. Well, if we have that data model inside of our landscape, basically, at least we have a very clear understanding on where information is coming from. Right? So we can definitely plot the path of all the elements which are going in there. So if it is being fed by, I don't know, let's say you have customer data and you have order data and both of them are being combined, but the customer data is coming from an online shop and the order data is coming from an ERP system, then there might be an inconsistency between these two. Right. Because there might be a mix up of data sets or not the right data quality, I don't know. So at least you know where to look at, right? So we don't know what data is being exchanged, but we know the data types or like the data sets in that sense. So I would say yes, it is definitely a good starting point for your investigation.

Stefan Opitz | Founder and CEO Codoflow [00:32:26]:

We at least help you to identify the areas where you should look first.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:32:31]:

We are always interested in looking a little bit also into your entrepreneur's journey. I would be interested in what obstacles did you encounter during the development and the launch of your coder Flow?

Stefan Opitz | Founder and CEO Codoflow [00:32:44]:

Well, I would say ask me what challenge I did not face. I think that would be a short answer. I guess everyone has challenges here and there and that's our daily life. But if I would really need to mark one or two challenges which are outstanding, I would say the first one would be UI and UX design. It is, as mentioned earlier, it is a complex problem and we try to build a solution which is so easy to use that the complex problem is actually more or less taken care of by the system itself. And you as a user just need to, well, focus on like providing the proper information and the system will guide you through the rest. Also we are acknowledging that let's say the majority of data architecture frameworks are relying on UML Unified modeling language, which is, let's say more software engineer approach of looking at well, systems data whatsoever. And we purposely said, okay, well we want to build something which is well readable for anyone, not just IT people or people with an education in that particular area, but actually even business users.

Stefan Opitz | Founder and CEO Codoflow [00:34:12]:

So we really, really put a lot of thought into that. And it sounds easy, but it was really, let's say it was not just one iteration, it was multiple. And I would say that was our biggest, biggest achievement to finally overcome with that. Not claiming that we will not learn along our path and even like, well, readjust it again because it is. That's how life works, right? You continuously learn.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:34:42]:

Well, it should work that way. If you stop learning, there's something wrong. And when you're done with it, how was the market response to Code of Flow in the beginning and since it's launched.

Stefan Opitz | Founder and CEO Codoflow [00:34:59]:

That'S a good one. So let's say, well, or you mentioned earlier, data architecture is not the most prominent topic in the world, right? So right now people would rather talk about AI. Well, trying to be nice here, right? So, and it's kind of like if you are getting in front of customers, we need to explain the problem first and then we need to explain that it is really Becoming a problem at some point if they don't do anything about it. And that is independent if they are using our system or not, it will just hit them. And there are studies showing that as well. So data architecture is becoming one of the, let's say prerequisites to be successful in the near future. So I would say that that was like the, let's say more challenging part when we are getting in front of them. But funny enough, I have not had one single person not confirming that the problem, the symptoms of not managing your data architecture and there are like many of them, like outdated documentation is just one of them them.

Stefan Opitz | Founder and CEO Codoflow [00:36:19]:

But just like trying to answer the question where is the data set coming from? I have, let's say the majority of people cannot really answer that, at least not without putting effort into that. And that was the part where everyone was like a little bit like oh okay, is there really a solution? And it's more like they cannot really believe it. And then we start actually explaining how our approaches and then you can feel like well if it would be that easy, why hasn't someone done it yet? Right. So it's really like a weird discussion and you really need to kind of like juggle the two sides and not making it too easy. And on the other hand like trying to point out like well, it is really a problem.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:37:06]:

I see Talking about the future here, we already discussed importance of code of flow or data architecture data management in particular when training AI, what impact do you foresee will AI have and what's your future plans for growth and evolution in the next few years?

Stefan Opitz | Founder and CEO Codoflow [00:37:36]:

Yeah, well, AI actually one, one part of our of our roadmap is to exp. Well, the model Context protocol which is basically allowing language models to you to use our system so that it becomes even easier to use and you can actually ask questions about the data model. So instead of asking an IT person where's the data coming from? You can simply ask the language model and then it will tell you that's one part of our roadmap which is kind of like answering the AI question as well. Because AI will become more and more part of our world. Like what I personally tend tend to say, it will make good people be twice or three times as efficient as they are if they are knowing the right questions to ask and if the data quality is right. And well, ensuring the data quality is right is exactly what we are targeting to do. On the other hand and well, another big milestone which we are trying to achieve by the end of this year is what we would call a so called deployment project. So I was just like pointing out that we will ask or we will send out these approval requests when you are trying to approve a release for a data change or data set change that might actually have implications, right? So if you are sending it out and you are asking 10 people and suddenly that might actually appear, well, okay, I not need to change my direct interface, but there's like three systems further down the integration stream.

Stefan Opitz | Founder and CEO Codoflow [00:39:19]:

There's actually an interface you need to change as well. And now you need to manage that further or you need to actually make sure that your changes are going online in the production environment with that change as well, which essentially is an orchestration challenge. So we put now in place this, well, we are planning to put in place this deployment project which is going to allow you to keep track on what changes are implied by your change and who else need to change that and start the design journey on their end as well. And then making sure that everything is like flowing together and well, kind of like a program management behind that. So that you are then making sure that all the necessary changes are going online in the production environment at the same time. And that is something I believe no one has ever done before because this is really meaning that you need to have an understanding between different environments as well, which we do from a data model point of view and background as well. So we are differentiating it between, between a development system versus a production system. Majority of development systems are not even integrated anywhere because you are just developing there.

Stefan Opitz | Founder and CEO Codoflow [00:40:43]:

Right. So if you're changing something in there, you're not. Well, you do not need to check that against the development environment. No, you need to check that against the production environment because that's kind of like where you're trying to push it into. And then suddenly you have like the real big picture behind that and you can start planning, I don't know, ERP upgrades, for instance. It's usually like, well, let's say a challenge to say the least. And now you have a completely different approach on, well, mitigating that risk of failing in the integration tests, which is usually come at the very end because that's usually the part which is developed the last. Does it answer the question?

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:41:30]:

Yes, it does. And it leads me to, so to say the final question. What advice for other founders would you offer to them? What key advice before or during venturing into SaaS space?

Stefan Opitz | Founder and CEO Codoflow [00:41:54]:

Well, obviously don't do data architecture because we are there, no jokes aside. And I guess I said it before, if you're trying to really change the world. Try to find a complex problem which you can solve in the most easy way you can possibly think of. It is the time for doing things easily. It's not the time of doing things complex. And I think that is like where a lot of people are having the let's say they have the right idea but they are trying to over complicate it, over engineer it. And I think right now is the time to actually make it as simple as possible so that you are capable of adopting it easily. Because a solution which is not adopted is not going to help anyone.

Jörn 'Joe' Menninger | Founder and Editor in Chief | Startuprad.io [00:42:53]:

Very smart words. Stefan, was a pleasure talking to you. Thank you very much for our audience. I would be interested looking back, is there anything you would have done differently in your entrepreneurial journey? Stefan, thank you very much again was a pleasure having you as guest and we will be back for our premium subscribers in the founders world with a few more in that questions. Thanks guys.