CAD, BIM, and the AI Leap: Qonic & Raven!

Fino: And we're live. welcome once again to another ⁓ of AI Across the Product Lifecycle. ⁓ I'm Michael Finocchiaro I'm your host, and I'm joined today by Moritz Rietschel Did I get that right this time? I think I did.

⁓ of ⁓ of Raven, ⁓ which is a cool CAD package, and also Chloe Guidi ⁓ of Qonic which is a well Moritz: Yeah. Fino: Moritz, you guys are in ⁓ Austria and Germany if I re recall. And ⁓ Chloe, you're in Belgium, so where it's a European ⁓ European edition right now. ⁓ so why don't you guys introduce yourselves?

So tell me about ⁓ Conick and Chloe a little Chloë Guidi: yeah, so hi, I'm Chloe. ⁓ I've been working as a software engineer at Qonic for about four years now. So I started there in twenty twenty one and that's also ⁓ when Konic was founded. So I've been there since the early beginnings.

before that ⁓ I worked at another company which was ⁓ or is still working on a cat platform. So I've been in the industry for about years now as a software engineer, so that's been very interesting. Fino: Nice. Chloë Guidi: ⁓ maybe a little bit about conic.

don't know if everyone knows what it's doing. ⁓ so ⁓ at Qonic we really believe that we should ⁓ democratize the BIM process because yeah the traditional tools they require ⁓ way too expensive hardware and it's really heavy software so we really started from scratch to build a BIM platform ⁓ that is cloud cloud-based ⁓ that is modern and user-friendly. ⁓ so ⁓ we really started from scratch to build that ⁓ such that you can ⁓ or everyone can model freely, that they can view massive models even in the browser performantly, ⁓ and that they can also enhance the data, ⁓ they can ⁓ verify and validate the data, so all of that ⁓ in one platform.

So that's what we build at COVID. Fino: Yeah, and I think you guys wrote your own graphics kernel too, which is really cool. Chloë Guidi: Yeah, ⁓ solid modelling kernel actually, yeah. Fino: Yeah, it's really cool.

⁓ Jacob showed me ⁓ spinning lun running around. It gets me a little bit sick, but that was really cool. so tell me more, it's about Raven. Chloë Guidi: Ha ha Moritz: Yeah, so ⁓ I'm Moritz, I was I'm one of the founders at Raven.

we s we first brought out Philip and Max also, so there's three of us. And ⁓ we first came out with a product a year and a half ago, so a lot younger incoming. ⁓ Fino: With Philippe, right? Mm-hmm.

Moritz: And therefore also we started out with a product that was AI first right from the start. So basically we had ⁓ this insight that a lot of the tools that are out there are ⁓ really useful and they're powerful but quite hard to like use and manage and you know get the skills to do to use them. So when we started out with Raven, it was really ⁓ supposed to help you use ⁓ complex tools like Rhino and Grasshopper ⁓ more efficiently and easier ⁓ and and quicker. And so now we've built out this platform that's like ⁓ very very good at you know supporting your ⁓ existing workflows with AI tools.

So they work across like a lot of different plugins, everything that I know Gasp connects to Raven can help you with so it can connect to Revit or tech instructures or ⁓ Archad and all these other things. So that was fast work. Fino: Awesome. ⁓ I would start with the first question about ⁓ looking back.

So, you know, the we've we've sort of had ⁓ we've had a moment, right? The open AI moment. There was before 2022, before everybody you saw this chat window and after. ⁓ were you guys skeptical or bullish when it when you first saw that?

Did you think like, ⁓ my god, the world just changed? Or were you like, I don't know, this is a bit of a fad, you know? Either of you can pick that one up first. Up to you.

Moritz: I guess at first it was ⁓ I I think i I would say I was curious more so than bullish or ⁓ thinking it was a fad. And and it was very bad at first. I I just distinctly remember that ⁓ th it would get all the things wrong and there were all these funny ways of like making it ⁓ tell you some something wrong or ⁓ like you ask it any kind of like factual question and it would just like hallucinate on something. So it was fun.

I think at first it was fun. Yeah. Fino: How about you, Chloe? Chloë Guidi: Yeah, I think for me it was a bit similar.

Like I was intrigued, so I really wanted to try it. Yeah, especially as a software engineer. I w always had the feeling okay, something major would come someday. So it was really yeah, you had this feeling like okay, ⁓ maybe this is it.

But indeed, yeah, while trying it, you quickly saw the limitation. Limitations ex especially for coding. Yeah. We realized okay, it's it's too soon.

⁓ so We could use it for for text generation and and stuff like that, but ⁓ other than that, it was a bit too soon to really start using it in in the company. ⁓ but yeah, we kept an eye on it. Yeah. Fino: No, I mean, did you guys see that it this did you see it as something as a game changer from the beginning?

Or you were like well, you you already said you were sort of a wait and see, right? Because it was so immature. And I suppose it's been such a surprise the the the the rate at which it's improved has been ⁓ really spectacular. ⁓ and ⁓ you mentioned, you know, you're you're a software engineer, Chloe.

I I I'm imagining that it's changed completely now in twenty twenty six, the way you develop software. So that That's sort of the second section is how how has it changed in terms of the tooling and also your behavior as a programmer? How how has it changed ⁓ for you at at Connect? Chloë Guidi: Yeah, yeah, exactly.

In beginning of of this year I think everything changed. Yeah, you realized okay, the yeah, the complexity of of the task that it can do has has gone up way more and it can solve tasks that would take us a couple of hours and that's the point that we also realized okay, we have to s really start adopting this in the company. So that's when we ⁓ started to use ⁓ cloud code for software development. So it's been working really well and and it really accelerates our process.

⁓ but we still have the feeling like okay, we are we are creating a very complex BIM application. ⁓ so it really helps us, but we still have to be very critical about the outputs because we need to develop something that is performant and scalable and yeah, it's not like a a small tool. So ⁓ we have to build something that is very good and so it helps us, but Fino: Hmm. Chloë Guidi: We also have to be be very critical about the output.

Fino: Exactly, yeah. same for you, Moritz, or has it been a little different? Moritz: So I mean before I get into maybe ⁓ you know building the car that's like ⁓ for me two and a half or three or three years ago I was in graduate school. So I was actually doing a lot of research very early on.

And back then ⁓ I was I would build very complex systems to like get LMs to do 3D reasoning and to model CAD and do all these things. And so ⁓ I distinctly remember ⁓ in early 2024, so two a little over two years ago, I built like a first ⁓ system that would bring LMs into into CAD and and it was really complex and the results were very, very like ⁓ you know you'd run it ten times and ⁓ before you see anything that looks like something. ⁓ but that was interesting because I I could kind of like guess at the future a little bit, you know.

Like at the time I was just poking around at ⁓ this weird new thing that's an LLM and like trying to find strategies to elicit the kind of thing that I was interested in, which is CAD. reasoning and so I could watch this progression of like every new model that came out and especially the one ⁓ in late twenty twenty four with the reasoning models with like O one preview became available. It was like it was like a giant leap for everything that I had done. And then so much of the scaffolding that I had built would just collapse into the model.

And I thought that was interesting. So by late twenty twenty four I like a full believer because I had seen sort of all the work that I had done just sort of collapse into the model and the model would do it on its own. And that was a big big change. So I would say, you know, in twenty twenty three or twenty twenty two when we first started interacting with ChPT and you'd ask it factual questions and get them wrong.

And that was kind of an early moment. But then within tw the year twenty twenty-four I saw it just explode in its capabilities and so much work that I had done just months prior had become kind of unnecessary that you know then I was like, Okay, this is like it's not stopping anytime soon and it's going gonna go pretty far. ⁓ which still doesn't mean that it would like you know, write software so much because I guess I wasn't interested in using it to write software, I was interested in seeing sort of the capabilities for it in CAD directly, not not to make CAD software.

So that's sort of the world that my mind was at. You know, two years ago. So it's been a while. Fino: Right, really cool.

How how has it changed the way you guys work as a team? 'Cause I'm trying I'm trying to imagine there you g must have agents showing up now for scrum meetings, right? I mean, since they're the ones actually doing the code. How how how has it changed?

⁓ I mean, are you guys both using ⁓ agile or or waterfall or some ⁓ some kind of mashup of the two? And how has AI changed that? How how is AI how are you putting guardrails on it as a developer and still leveraging it ⁓ on a daily basis? Go ahead, Mort.

So you seem to have wanna talk. Chloë Guidi: Yeah you can go ahead, yeah. Moritz: Well, I mean, ⁓ it's a very interesting question and it's also something that you have to continuously reevaluate, right? So not just as the models and the harnesses change, but also ⁓ maybe you learn things using them and you figure out what works and what doesn't.

And I guess I'm just reading reading a lot more code than I used to because ⁓ I there's so much more code being produced, but now like Chloe said, right, you need to be very critical. ⁓ of the output and and then really evaluate it thoroughly. So that's like a big change that I see. ⁓ it's a lot more review, ⁓ which is also a lot of work.

Chloë Guidi: Yeah, yeah, true. Yeah. It's not like yeah, at the moment it's not like we we really let it just solve tasks without us looking at it. So that's something, for example, we had a look to to incorporate it in our in our exception follow up.

So when there are issues ⁓ coming by customers that that are using it, to have a look like okay, this is ⁓ something that the customer was trying, ⁓ maybe ⁓ Fino: How about you for you, Clay? Chloë Guidi: It can just solve it by itself because these are sometimes small issues. ⁓ but then we ⁓ quickly noticed like okay, it's not always solving the issue correctly, and or it's maybe solving some no-reference exception to maybe not go too technical, but yeah, that's not the actual issue.

So ⁓ that's when we realized okay, we should use it a bit differently. ⁓ so now we are using it to make summaries and to maybe assign. the correct person to look at it and to propose something, ⁓ but then someone still really checks it and has a look whether it's actually correct and but also there it it really helps us to to remove some some work that otherwise had to be done manually. So there it really helps us.

⁓ but we still have to interfere ⁓ ourselves. Fino: So it's good to get rid of some the mundane stuff and yet you still have to keep an eye on it because it can still give you a pink elephant once in a while, which you don't want. ⁓ that's cool. And I was ⁓ that sort of leads into the next s action is I think that a lot of people that are not very close to the startup world or close to engineering don't realize how much AI is a part of everything.

And and so I'd like to ask you guys like Chloë Guidi: Yeah, definitely. Fino: In your software, in Raven and in Qonic, where does the AI sit? Is it at the user interface level in terms of you know there's a chat bot and you're asking it to do stuff? Is it part of is there a foundational model where you've taught it how to build a building or to, you know, draw ⁓ do rhino?

⁓ or is it the entire DNA? Maybe you've also put it all through up and down through through the stack. Where is AI actually implemented in the software? How in other words, how's the DNA of software in 2026 changed from the DNA?

⁓ pre twenty twenty two or t even twenty twenty four, because it's really the Cloud Code and I think it was anti gravity might have been the first like pretty awesome agen decoder and then quickly replaced by Cloud Code. Anyway, I'll let you guys answer. Morris, you seem to have a ⁓ wanna talk. Moritz: Do I always like it?

Okay, I mean look we built a software that was from the start about interacting with AI and and so obviously it's part of every every bit of the software. What I think is is interesting is that there's kind of two ways to deal with coding models. And then one of them is like, ⁓ I am making the software already, now I can code with ⁓ agents so I can make the software faster. Which is like very good, that's what's happening everywhere, everybody's gonna be more efficient, write more software.

But the real like us the real thing that changed or like the thing that we are seeing and how we think about this problem and because we're such a young entry I guess also into the space is we are working with those models. We're not using them to like build a thing and then ship something that has no AI in it, right? That's kind of like we're not just building something faster than was already possible before, but we're just doing something completely different. Like the product that we do makes absolutely no sense without AI.

So yes the AI is at every level and I also think that that's just a different kind of category, right? It's like an AI application and not an application written with AI. So ⁓ that's just what we are. Like our DNA is ⁓ making AI work for you and your design workflows and and we have AI at every level.

Fino: How about for Enconic? Chloë Guidi: Yeah, yeah, I think yeah, our point of okay, we are not not an AI application, but I think our point of view is a bit similar that ⁓ we really want to embed it like in the product, like not just one one chatbot or or just to for example, other tools they use it to generate some ⁓ to D images or we really want to go further than that because yeah, architects they we we believe that they don't spend their time modeling but they lose a lot of time in ⁓ doing quality checks, ⁓ doing clash detection, checking whether the quantities are right.

⁓ so if we can incorporate the intelligence really in the whole application and in the tools while they are modeling, ⁓ then that way they can they can solve and and win a lot of time. Because nowadays yeah they have to model, then build, then then fix it, and then the fixing is always ⁓ afterwards. So if we can incorporate that in the tools, they can lot of issues can be prevented. ⁓ and this what what we want to do with Qonic is is to make these tools intelligent enough to already take into account ⁓ all the compliances while while modeling or to already say without someone asking for it, maybe this quantity is not correct, ⁓ have a look at it.

⁓ and this way ⁓ this can really help ⁓ help the users ⁓ to To get better models and get better ⁓ quality of the models. Fino: Another thing I've been thinking about a lot because of all these changes is also the the economic model, right? Because it's expensive. I mean, cloud code, I don't know how much it costs me w more than I even want to say online ⁓ every month.

⁓ how how how are you guys dealing with that? Because that's g for as a startup using AI, that's d definitely a consideration. Like how are you gonna offset the cost of the cloud? 'Cause obviously these solutions are running ⁓ you also have to pay at WS every month and you've got to play a cloud c ⁓ cloud code bill.

How are you guys leveraging that? Or you know, are you doing ⁓ be bringing your own LLM for users so so that they can get some of the things or thinking of doing your own financial model so you don't have to pay anthropic for every single click? I mean, how how are you trying to rationalize that in in your products perspective? Chloë Guidi: I'll go first this time.

⁓ yeah, that's a good question. ⁓ so I think we definitely ⁓ are also checking MCP. So I think at that point they would use their own ⁓ account ⁓ or would be able to use their own account. ⁓ but for the other pricing I think we are still in are still developing ⁓ like more the the usage of of the L L Lemma as well.

So I think for pricing wise we still have to Fino: Moritz, you okay, go for it, Chloe. Chloë Guidi: investigate a bit how we will tackle it, but it's definitely a relevant question, ⁓ how to how to set the pricing. Fino: Yeah. And Morris, how about you?

Moritz: ⁓ ev obviously very central to our business case ⁓ and offering. there's a couple of different things. ⁓ one of them is ⁓ we don't have ⁓ the ability that you can bring your own keys as a normal consumer but as an enterprise you can. So ⁓ and because enterprise advertise of you have these contracts with like Azure, OpenAI or Google, Gemini enterprise contracts.

So they can do use that. But on the other hand, like one thing that makes Raven very compelling to most of our users is that it's very easy to just set up and used, right? So you don't need another subscription, you don't need to hook it up with something, you can just like download it and get get in. So for us, like maintaining that ease of use is super important.

And I think There are a couple things to consider, like the way that it works right now is not necessarily gonna be the way how it works in the future. Maybe ⁓ the L and Ms that are really expensive right now, you would get the same level of intelligence cheaper or if you're an open source model or something like that. ⁓ maybe eventually you can self host on a you know a good computer, ⁓ a model that can achieve the stuff that big models are required to do right now. ⁓ I especially in the last few months you've seen we've seen a lot of really cool releases from Google, for example, Jamma for stuff like that.

⁓ where you can really see that they manage to scale down and maintain a lot of the reasoning capabilities. They lose a lot of the factualness, but we don't really mind that because we're doing the cat stuff right. So ⁓ as the field is developing, I think ⁓ we're just like we have a solution that's working for us right now, but we're always monitoring sort of how that changes. ⁓ and also how sort of the spending structure of AI tools and and firms in the field kind of ⁓ adapts.

So yeah, hard to say what the future brings, but I think there will be a lot of different models and a lot of different ways to leverage tools like Ray. Fino: And I think ⁓ maybe less of a concern in in construction, ⁓ but nonetheless I think another issue is the lack of traceability and identity management with MCPs. I mean you mentioned MCPs, Chloe, but there is no protocol for or standard for tracing the who used the MCP and when and what data they used, right? I think that the there's something fundamentally flawed in the current implementation that that needs to be fixed in terms of identity and Authentication.

⁓ I wanted to ask too. So, you know, we've now four years into this AI revolution, right? Since ⁓ OpenAI ⁓ opened the floodgates. ⁓ I I I think I may have seen an open AI moment in the manufacturing world at Prove It when I saw them deploying entire factories with OT with using Kubernetes and Git within minutes, and I was just blown away.

I'm not sure I've seen that engineering. I don't think we've really had. a before and an after moment. And maybe we won't.

⁓ so do you guys think that ⁓ we're gonna have an open AI moment engineering and or BIM? And ⁓ what do you think it's gonna require to get there? It it because and and do you think it's like six months away, two years? I mean, it's hard to say, right?

Because it's everything's changing all the time. But it feels like our jobs and our industry is hard, right? CAD is not easy and and so I I'm wondering how you guys ⁓ what do you how you gonna react Moritz: Can you guys hear me? Chloë Guidi: Yeah.

Moritz: Okay, sorry, I just thought the audio cut out. Okay. So I think it's gonna happen. ⁓ because but the reason why you haven't seen it happening is also because nobody has had a focus on it.

So ⁓ it happened in coding and you know, like I mean it's it's still on ongoing but ⁓ and a lot of that has to do with the focus ⁓ that the labs put on coding. So there are many different things you can do with a reasoning model to ⁓ like you know, train it on on different tasks, but it's very easy to do it on coding tasks. 'Cause they're verifiable, you can ⁓ you know, run a reinforcement learning loop over a certain ⁓ set of problems, you can ⁓ judge ⁓ whether a code is better or worse than another code using in some way, anyway.

And so there's a lot of style questions and evaluations that are easy to do for code. You could do them for engineering, specific engineering tasks. It's just that the focus hasn't been there. But I think in the last six months you've seen a lot of money going into sort of ⁓ Physical AI startups, ⁓ like Bezos has this like been higher, like project politics with like billions of dollars in funding.

So ⁓ I'm not saying that they're gonna like solve CAD or something, but in the past year the focus has been elsewhere or like two years. ⁓ for example, OpenAI didn't put such a big focus on coding, and that's why Enthropic ⁓ has sort of like outgrown them, right? Because ⁓ Enthropic went all in on coding, they didn't really mind all the other things, and OpenAI is still publishing like, ⁓ we found it ⁓ we solved a new ⁓ Like an existing other support problem, or if they're interested in like protein folding and all these like very broad research terms, whereas on topics just sprinting forward with just coding.

I mean they're not even good at vision. They just do coding. But it really paid off for them because they were you know, they picked in a ⁓ a wedge kind of and went all in. And so now everybody else has to be great at coding because you're compared to entropy.

⁓ and that can happen for any other domain. So what you've seen with Gemini is that they started focusing on SVG generation a few months ago, which I think is like a step into the CAD world. Of course they use it for like web interfaces and stuff now but structured SVG is really 2D CAD, right? So going in this direction, I don't know where it comes from.

I don't know if it's gonna be one of the existing labs or something, but the focus on engineering will happen because people realize that there's this big market there. and it will be different. Like The AI will be will have very different capabilities from what we see right now. ⁓ it's just hard to know you know where it's gonna come from.

Fino: That's interesting because ⁓ you guys probably saw that last week MEAI, which is an Austrian ⁓ surrogate modeling startup that I've actually had on my podcast already, ⁓ they were acquired by Mistral. And that's especially interesting because Mistral is providing the AI back lane for DASO systems ⁓ portfolio as well as ⁓ contact software, the German ⁓ PLM. So Moritz: Yeah, exactly. Exactly.

Fino: It seems that at least Mistral is trying to get that wedge in terms of engineering, which is super interesting. And the other thing you made me think of more, it's is that ⁓ I saw a post ⁓ that someone was reading ⁓ between the lines of what Jeff Bezos was talking about in terms of Prometheus, because that's what you were referring to. And he actually is talking about CAD. So it's a little, you know, I'm not sure what's happening there, but I think that it that whole open USD, you know, because you're trying to model the f the digital twin of the factory, closed dupe optimization.

They might actually be looking also at ⁓ at that CAT Foundational Model Two. So it's gonna be an interesting year, right? ⁓ Moritz: Yeah, absolutely. Absolutely.

I think I mean it it makes a lot of sense if you think about running these loops where you have the agent model something and you can evaluate it ⁓ and then improve. Like you can do that for CAD. You can have it model, ⁓ you know, solve an engineering problem and then run it run some simulations on it and stuff like that. So Amy, Mistal, Mises like it makes sense to build these loops.

The question is like who's gonna do it in what industry for what vertical? But I it's totally possible with what they're doing today with coding. You could just map it to a different discipline. Fino: Yeah.

And Chloe, ⁓ I'd direct that to you too, and and I'm I would think about ⁓ the other big acquisition last week was Twin Thread being acquired by Aviva. Now Twin Thread was already a partner of Aviva, but the outright acquisition w came as a bit of a surprise. ⁓ which signals that open USD is really becoming a big deal. And I'm wondering, ⁓ in the So you what OpenS USD is all about building digital twins and having a feedback loop that's in re more or less real time.

Is that something that also the BIM world is looking at? Are you guys trying to get to the point where you design the building, the building gets built, and then as ⁓ the building's being used, feedback's coming in and ⁓ well, maybe the next time we design a building that in that s similar area for that same customer, we might need to make these other changes. And so you're getting sort of a feedback loop. Is that something that could happen, BIM or or not?

Chloë Guidi: for me as a software engineer it's maybe a bit difficult to to reply ⁓ on that question. I guess so. I think ⁓ yeah, if you have all this information and and now you can you can incorporate that ⁓ in your flows and and learn from it, I think it's ⁓ definitely something something you should be able to do. ⁓ is it something that that we are looking at?

I think I think not yet. ⁓ I think we're not there yet. ⁓ I think there's a lot more things that have to be done maybe first. ⁓ but yeah, that's that's just ⁓ that's just how I look at it.

I would have to check with the with the real ⁓ like the more product people to to to know what they think about it. ⁓ but yeah, I think it should definitely be possible. Fino: Well well I didn't give you I didn't give you a chance to ⁓ answer the initial question about just the open AI moment for engineering or for BEM. Do you think we're there or you think it's coming or you think it'll just there'll be many moments and not just one?

How how do you look at that? Chloë Guidi: Yeah, I I think like like Moritz was saying, like I think definitely something is changing. ⁓ also because I think for for the BIM world then ⁓ you have like we are also focusing a lot more on on these open standards. So you have also much more the data becomes more open and ⁓ compared to the tools where like all the data was kept inside.

⁓ so d this also makes it lot more possible to to really train on the data and and to make the Yeah, make the data more more more ⁓ yeah, more that you you have more information so you can also build better tools around it. ⁓ also I think tool to tool interaction becomes possible that way. And I think that also becomes very powerful that you can scan a PDF and ⁓ get all the specifications out, pass that to the Bim BIM tool, which can also ⁓ leverage that. So I think yeah, you start to see these possibilities and I think that the customers also start to see them.

⁓ so that way I think bit by bit I don't know whether whether it will be like a really turning point. Maybe there will be, but ⁓ definitely something is is shifting. That's something we really see. Fino: And ⁓ I think that the in the demographics of the people that watch this show, I have ⁓ maybe twenty to twenty-five percent are really entry level.

⁓ and I can imagine that those kids are having a bit of anxiety because they're like, you know, AI is gonna take my job. ⁓ in terms of you as a software developer and you Morris as a founder, what kind of advice do you give to that younger emergent generation, the ones that are coming out of university looking for jobs? How what do they need to focus on? So they're not immediately replaceable by an agent.

Chloë Guidi: I would I would always say like stay curious, try it out, ⁓ don't pretend like it's it's going to go away because I don't think it is it it is is is is not going to go away away anymore but ⁓ I think as long as you as you learn to to handle it and and learn how to how to ⁓ yeah how to say learn how how to use it properly and also I think maybe also be critical about that because you see a lot of things passing by but ⁓ it it doesn't always work. Like there's a lot of tools for example that say that ⁓ we can do this and that and and then you try it out and it doesn't really work.

So I think it's important ⁓ that you also see the the benefits of some tools but also realise okay some tools don't work. So ⁓ But you can only figure that out by trying it and ⁓ by staying curious. I think that's important. Fino: So fluency in the AI tool is super important, right?

⁓ Moritz Moritz, what what would your advice be? Chloë Guidi: I think so, yeah. Moritz: ⁓ I I I I would say I get it. I get the anxiety and I also don't know if anybody really has the answer.

Yeah, first of all, honestly. I do think that ⁓ engaging with the tools is probably the most important thing. if if tools are gonna change the workflows that it might make you feel like they're gonna take your job, but what's probably gonna happen is that the the job and like the skills and the things that you actually do are gonna be slightly different. So like Chloe said, instead of writing all the code, you're gonna have to review a lot of the code.

So it's it's super important that you're creating coding and you understand the code, but the job looks very different, right? So I think that's true for a lot of areas and I don't see currently, you know, at the current capabilities they are replacing engineers. I I don't see that. ⁓ but I do think if you if that's something that you are worried about then you need to probably sprint to the front of of this wave and and and figure out sort of what this how do the skills change and what is gonna be really important.

⁓ So that's what I think. And I know that it feels very scary to recent graduates because they think that ⁓ the entry level jobs are the ones that are falling away. I also want to remind people that young people are usually very good with new tools, they have very good like meta models of how this stuff works, they can get experience, they are ⁓ you know ⁓ still very adaptable to new skills. So I'd say I'd say embrace that as sort of your strength instead of ⁓ it being sort of your ⁓ opponent, you know, like AI is the thing that you're gonna you can be good at.

You can be the person that's good at this, ⁓ and that's gonna be a differentiator. Fino: Right. Great answer. Thank you, Moritz.

actually we do have a question in the in the chat from Janelle Pierce. And she asks, ⁓ any advice on how we can better influence AEC decision makers to move beyond viewing AI, BIM, and digital twins as isolated technologies and recognize them as fundamental to the future operational resilit resilience, efficiency, and competitive advantage? What do you think, Chloe? Chloë Guidi: I think yeah, I was checking Moritz is maybe lost.

He's not moving anymore. Fino: ⁓ he's not connected? Okay. Chloë Guidi: That was long question.

Fino: ⁓ sorry. Well, I think she's just saying how can we influence decision makers so that they can realize that we're not, you know, these all these things are connected. The digital twin and the infrastructure and the eye, these aren't three separate questions, they're the same question about improving resilience and efficiency and competitive advantage for ⁓ for firms, right? Chloë Guidi: Yeah, definitely.

Yeah, I think ⁓ if you if you use it and you can enhance ⁓ the quality of your model and and in yeah, in BIM context of course, ⁓ and your model can become the single source of truth, I think a lot less mistakes are made ⁓ for for construction world as well. So I think if you start using that and you and you see that, I hope the decision makers also ⁓ see the added value of that. ⁓ And then you can incorporate it. But you can also start doing it bit by bit.

Yeah, we have customers that start using it for for one project and and then see ⁓ if it if it actually works. ⁓ so maybe with some proof of concepts. ⁓ it's not like you have to immediately shift your whole company. It's also not not what we do.

So you can you can start trying it out and ⁓ try it on one project and then ⁓ if that works incorporated further. That's what what Fino: So it's really a argument of ROI then? Of just trying to ⁓ make them understand the ROI that they're getting out of it? Potentially.

Chloë Guidi: Yeah, I think I think that was would be the best way to work. ⁓ yeah, no one wants to use something that yeah is adding more complexity or ⁓ also I think using tools that really ⁓ make it transparent what is actually worth doing, what it's actually doing. I think that's also important. ⁓ that's also something that we want to focus on, that the output is is clear and that you don't have to ⁓ spend more time on checking whether the result of the I was actually correct, but that you can quickly see what it actually did and that you still have the you can still grasp what it's what it's outputting.

Fino: Well, I asked in the in LinkedIn, I have not heard back from Moritz. We hope that everything's okay with him and he'll join us. ⁓ so then the I and it the the next question is ⁓ more about digital maturity. ⁓ like when you're working with the customers, ⁓ and typically ⁓ AEC is one of the least mature ⁓ industries.

I I usually think of Digital maturity for companies being on a scale of like one to five, where ⁓ five is the most ⁓ the most mature, you know, like adaptive ⁓ digital twins. And if one is people are still using email and Excel most of the time. ⁓ I suppose that ⁓ most of the customers ⁓ you're dealing with. Hi Moritz, glad to see you back.

⁓ yeah. Moritz: To open a new and like re enter the studio as a new person somehow. Okay. Fino: So I was asking about digital maturity.

So when I think about digital maturity, I think about ⁓ companies that are not mature, that are using Excel and and and email still for collaboration of being like a one. And I think of the mythical company that has all autonomous agentic digital twins, you know. ⁓ where does most of your customers sitting? Are they closer to one or some of them at three?

Wh where do you see your customers today? Chloe, you want okay. Moritz: ⁓ very good question. I think ⁓ yeah, sorry, I'm just more jumping.

⁓ we see everything. and it's interesting because what what we see sometimes is that people who are at very low digital maturity will use AI as like the moment where they do embrace it in a way. If you know if that makes sense. So even though they maybe have been very sort of low-tech ⁓ for a while, now they sort of see that as like a leap drop opportunity.

Right. So I think that's it just Fino: Okay, thanks. Moritz: even for people like even for less technical people for example, because it's ⁓ un unlocked on the like sort of skills. Fino: Yeah, I I was gonna get to that part in the second half of the question, but what about you, Chloe?

Did you have some feedback on ⁓ on the maturity of the customers you you talked to? Chloë Guidi: Yeah, I think for us it's also I think in general, yeah, we also see it see a lot of different things, but in general it's also low to medium, I would say. ⁓ but I think it's also related to the traditional tools. Like there are al always like ⁓ only a few experts in the companies that that can actually use these tools.

⁓ so I think ⁓ by creating these modern tools, ⁓ this this shift is also starting and and also through AI they they start to see Fino: Mm. Chloë Guidi: maybe a bit like what we were discussing before, like they start to see, okay, this can actually solve ⁓ some workflows and solve some tedious, error prone tasks that we've been tack have having to tackle. ⁓ so bit by bit this this shift is coming. So ⁓ there's really a momentum going as far as we can feel.

⁓ so I think this digital maturity will s will definitely improve ⁓ Fino: Well my my thesis is that ⁓ companies that want to move that needle further to the right towards a five ⁓ much more likely to do so using that are powered by AI like Qonic or or Raven. If they're depending on Autodesk or or Z Mans or PTC or DASO to do that digital transformation, I think two, three years later they're still waiting for it. You know, even now they're waiting, right? Because we've AI's been around and all we're getting is May more or less co-pilots, which are so 2024 now.

so I'm wondering, I have in your experience when w when the customer sees all that they can do inside of Raven Arconic, thanks to this AI, is there a bit of an epiphany? Do they go talk to their colleague? Like, did you see this? What we can do if we, you know, had ⁓ more we were more mature and we didn't have data silos and the guys in engineering talked to the guys in manufacturing and The designers talk to the people in the field, you know, we'd actually be able to do business better.

have you ever seen that? ⁓ had an an you know, a real impact on the business? Chloë Guidi: I'll let you go first. Fino: Ha ha ha.

Moritz: Sure. ⁓ yeah, yeah for sure. So one big thing that ⁓ I can mention here is Rhino Inside Revit workflow, so bringing Rhino stuff into Revit and make families and stuff. So ⁓ Rhino has built this Rhino Inside integration and ⁓ It's very, very good and very, very hard to master because not only do you know need to know all the stuff that you already need to know about Revit, but now you also need to know the stuff about Grasshopper.

So it's kind of like this o overlapping expertise field that's very small. ⁓ but it's extremely useful because all of our customers in the AC space have these workflows. ⁓ Now with r Raven, you can generate new ⁓ like ⁓ files, ⁓ code that does this transformation and then also ⁓ you can use other people. So you no longer need to be the one expert that can that they can author your script themselves and and use it, but you can take someone else's script and like ask a question about it.

And so even though the tools have been around, just being able to use them with Raven by your side is like a massive unlock. So that's one of the things where it's like, ⁓ you know we've been trying to even the digital digital mature ones like ⁓ we've been trying to push this and push that and there's all this friction around ⁓ implementing new tools and you know less data silos and so on. But ⁓ AI is kind of like ⁓ the oil in the gears that can like actually make the machine run how it was supposed to ⁓ on the power on the on like the PowerPoint slides from 2020.

Fino: Nice. I like that answer. How about you, Chloe? Chloë Guidi: Yeah, yeah, yeah.

Yeah, similar. But yeah, I think for us not not only AI, but like also the fact that they are using user friendly tools ⁓ also helps. Like for example, we also believe in like the fact that like this licensing model of that you can have unlimited users to to make it really accessible for for everyone in the company. For example, we had a customer that like only one person was using it and then bit by bit the others we s really started like to see a a ripple effect where more more cust more ⁓ employees of that company were using it.

⁓ probably because it was also looking way way more user friendly for them. ⁓ so that also really helps. ⁓ but yeah of course through AI ⁓ it becomes also a lot more easy to use. ⁓ but other than that I think ⁓ also through I I think I mentioned before, but that like through leveraging ⁓ this data quality and ⁓ you have less like garbage in, garbage out than than with the classic tools.

And then they also feel more ⁓ more maturity of the of the model and of the of the product. ⁓ and therefore there is more interested interest to also really start using it. ⁓ so I think I think that really helps to if it becomes more reachable to have also more digital awareness throughout the the industry. Yeah.

Fino: Nice. Chloë Guidi: ⁓ I don't hear you anymore. I Moritz: ⁓ I think you're muted, Tina. Fino: Oops, how's that?

Better? No, I said I I think that validates my thesis that startups are a better place to s to ⁓ to count on ⁓ digital transformation ⁓ particularly if you want an accelerated ⁓ version of that, right? ⁓ that that's about all I had in terms of questions today. I wanna I was curious, ⁓ in terms of ⁓ people wanting to meet you guys and wanting wanting to learn more about your solutions, where where can they do that ⁓ over the coming months?

Chloë Guidi: I think ⁓ for us, go ahead. I know. I'll go first this time. ⁓ for us, ⁓ I think so some important ones for us is ⁓ in October ⁓ we will be at the Building Smart Summit in Tokyo.

⁓ there we will also have our own ⁓ conic talks, ⁓ with some dedicated sessions about conic ⁓ for who is interested. And ⁓ yeah, yeah, yeah, yeah. But we also have something a bit more close by. ⁓ so here in Belgium, in Ghent, ⁓ Moritz: Yeah, so Fino: Okay.

Nice. In Tokyo? That's cool. Chloë Guidi: In our hometown, ⁓ we will also do a conic talks event ⁓ twenty-seventh of October.

So everyone is definitely also welcome to join that. Fino: ⁓ okay. ⁓ looking forward to my invite. How about you, Morris?

Chloë Guidi: Yeah, yeah, yeah, you will. Moritz: Yeah, so ⁓ we have ⁓ on our website we have like a list of things ⁓ where you can meet us. I'm not gonna go through all of them, but ⁓ I can already say in the next next week and on Monday we are putting on a rhino user meeting in New York together with SOM and McNeil. So we love the Rhino user meetings in Europe.

⁓ they don't really happen in the US, so ⁓ we asked the McNeil guys about it and they you have to make it happen yourself. So on June first, if anyone's listening is in New York, ⁓ you know come by. and then we're gonna be at a Fino: Nice. Yeah.

Awesome. Moritz: A couple other you know performing conferences. We're going to Acadia, which is in September, ⁓ in the US, ISS in Toledo, which is in Italy. These are kind of more academic conferences and then ⁓ AC Tech of course in the in Europe again, these kinds of places.

⁓ we're not gonna be in DC now. Fino: Are you doing ⁓ the C D fam in D C? Are you guys gonna do the Okay. Cool.

Well ⁓ I hope that ⁓ sorry, go ahead. Moritz: But No, I w I mean we always ⁓ we have like if you wanna meet us, go on our website, scroll down, there's like a list of events and you'll find something, I hope, near where you are. Fino: Right. I'm I'm still ⁓ planning to do one in in another event in in Munich before the end of the year.

So I hope that I'll see you guys there. and ⁓ once again, thanks to the audience for joining. We hoped we had a a good audience today. ⁓ a shout out to the sponsor, ⁓ AWS.

Please download the white paper. ⁓ I think there's actually a video associated with that. I'll put the link in the in the comments. And ⁓ once again, a big thanks to Moritz and to Chloe for for joining me today.

I really appreciate your ⁓ openness and and all your answers. Thank you very much. Chloë Guidi: Thank you for hosting. That's very interesting.

Moritz: Yeah th thank you very much for hosting us. It was a great conversation. Fino: Yeah. And so ⁓ stay tuned.

This will be published up on YouTube pretty soon. And and we'll talk to you everybody later. Thank you very much. Have a great day.

And ⁓ for folks that are watching and on LinkedIn, you know that in about an hour and fifteen minutes I'll have another one of these, but with ⁓ supply chain ⁓ startups, Omne and ⁓ Barden is gonna be a really cool discussion too. So thanks to everybody. Bye bye.