From Satellites to Software: Valispace's Impact on Engineering

In this episode of the CTRL+Listen Podcast, we chat with Louise Lindblad, CPO and Co-founder of Valispace. Discover how Valispace, a transformative software platform, is reshaping engineering workflows through enhanced data management and collaboration across various sectors, including aerospace, medical, and automotive industries.

Louise shares her journey from developing satellites and drones at the European Space Agency to revolutionizing engineering processes with Valispace. Learn about the challenges of outdated tools in the industry and how Valispace's innovative approach helps engineers manage complex hardware product development more efficiently.

Episode Highlights:

Integration of AI in engineering
Impact of regulatory environments on cloud-based tools
Emerging challenges in engineering design space
Trends for Next-Gen Engineering Tools

Links and Resources:

Learn more about Valispace here

Connect with Louise Linblad here

James: Hi everyone, this is James from the CTRL+ Listen podcast, brought to you by Octopart. I have my co-host, Joseph Passmore here today. And today we are joined by Louise Lindberg. She is the CPO and Co-founder of Valispace. Really fascinating company that's doing some exciting work in the design space. Thank you so much for coming on the show.

James: To start, do you wanna just tell people a little bit about the company, what your product is and, and what your goals are?

Louise: Sure. So my background is in space engineering. So I, I studied physics and aerospace and started working then in this, in the satellite industry. So I was kind of a, a systems engineer for, for satellites building both big projects and small projects. And what I found when I worked in the industry was that the tools that we used, or the way that we handled data was very outdated, right? So we used mainly Excel sheets and word files and PDF documents to send requirements to each other, to send designs to, to work on the data that we, that we need to build this satellite. And the, that's why when I met my co-founder Marco, we basically decided to do something about that, right? So we said there should be a better way for engineers to collaborate on the data, to actually share data with each other, and there should be a better tool that that does that. So we started this projects value space. It came out of a, an event actually, which was called Startup Weekend. So where entrepreneurs meet and kind of discuss ideas and, and work on that. And we really thought this could be something really useful for, for engineers in general. So we started working on the product and, and today we basically have a, a full product. We have over a hundred customers using, using our tool and anywhere, like we started the bit in the space industry because that's where we come from, but now we have customers anywhere from the medical industry to aviation to, to automotive, right? So we always knew from the start that it's not only for space engineering, but in general improving the processes of systems engineering and requirements engineering. In, in the engineering industry, were, well where people build complex products, let's say,

Louise: We, we've always had this vision, right? So we, we even did a, a video 2016, I think, about this AI assistant that would help you kind of figure out how to optimize your project, right? So the idea was to make engineers more efficient and also have like a, a way to help you in your decision making, right? But we never found that the technology, well, the technology has been there, right? But we didn't have the resources to actually do something about it ourselves. And then yeah, in late 2022, right when chat GPT came out and, and everyone, it was a bit of a hype, right? We said, okay, this actually, both me and Marco started trying it out and we said, this actually works really well on requirements. So requirements is basically is usually text-based, right? And these kind of large language models are really good at handling these texts and helping, helping the user improve the requirements, review them, et cetera. And we said, okay, now it's our chance to actually make something real in our product that would help our users. So we basically launched what we call the value assistant, which helps the engineers along the workflow, along writing their requirements and specifications to doing the actual system design to verifications and helps them along all that life cycle to actually be more efficient and take better decisions. So, and I think we're just stretching, scratching the surface here, right? You ask how does, how will this affect engineers' lives in the future? I think it will have a huge impact. I think in 10 years from now, engineers will not work the same way that they do today, and it'll be because of these new technologies that are coming and because of these yeah. AI trends that we're seeing now that we will have a diff very different way of working in the future.

Joseph: To, to follow on that does it, so it functions like a design assistant and how, how does that help with the design process?

Louise: So there, there are two, two main things, right? First, you make the work more efficient. So for example, instead of having a full design review with hundreds of engineers looking at the requirements just to see if the text is correctly written, right? If you, they're using the word a shell or should, there are some standards that you have or that you should follow in this kind of way of writing requirements, right? So if you use AI to actually improve those requirements or help you to break down those requirements or help you to e even generate those from the start, right? So if you have a specific need, you say that I, well, I want a car that can drive this fast, that uses electrical power, right? That, that's has a specific set of needs, right? The AI can even help you to start with a set of like generated requirements from that that you can improve on. So that's the first thing, right? To make you more efficient by letting the AI do steps of the process for you, right? So you don't have to do all of the things manually. You can automate a lot of things. The second part is being more effective, right? So actually taking better decisions and being more innovative in your, in your design choices, right? So for example, if you have, well, if you, if you have selected if some components for your, your PCB board, right? But you know that, well, in, in a few years this will will no longer be manufactured, then the AI can help you, right? To say, okay, what are alternatives for these components, right? So you basically have a, a way of taking better decisions by having an AI having more context of what you're trying to do and bringing all that together to help you optimize your, your process or your, your design rights, your products.

James: I, I was gonna ask, obviously this is really helpful for, for saving time and efficiency and that sort of thing. Is this more of a surface level, a low, I guess like a lower end type work as opposed to the highly complex side of, of, of engineering? So with the where of technology is that right now with ai, obviously it's, it's in that space. Is this something that's gonna get more complex as time goes on?

Louise: So I think there is, well, the reason why we need to have such big engineering teams today is because the products are complex, right? If you wanna build a rocket or if you wanna build a satellite or even a, a flying car, it's a very complex product, right? So you, you have a lot of parts to it and you have a lot of requirements on it. You have a lot of things that need to be thought through. And the reason why there needs to be a lot, so much work and coordination is because obviously no one person can have all of this information in their head and know exactly if I do that change, if I change the number of batteries in my battery module in the electric car, what does that mean for my whole design, right? What do I need to change? Who do I need to contact? So that's why also mistakes are made or that's why mistakes are discovered late in the process and that's a problem. But with AI or with these kind of models that you can train, you can have something that has more context or has all the context actually in, in, in that, of that process and of the thing that you're building. So you can actually start for the user having the things less complex, but they are still complex, but you abstract kind of the complexity, right? Right. So that you can take decisions that are more useful while you still know that there is the, the changes that you're making, you know, the effect that they will have on, on the whole system. Right?

Joseph: Could you tell us a little bit about the role of data security in cloud-based engineering tools?

Louise: Sure. So I mean, cloud is a, is a big topic, right? I think definitely cloud is the future. We, we have a lot of customers actually that are, especially in these kind of regulated industries, right? In the us there are ITAR regulations in other countries, other types of regulations that don't allow the companies to put data on, on the cloud or, or at least they have to use the gov cloud or, or these kind of things. We are seeing some companies get a bit more relaxed on it, but I mean obviously if you have government regulations you cannot do much about it. But that's why these kind of solutions that gov cloud, like there are works on something similar for Europe as well going on, right? So I think cloud is there to stay, but the security around that is something that we're still, well we as in all, all of us in that are working on this are, are working on in the meantime. So valley space is, we, we always, we, we don't say that it's a necessarily web based application. It's browser based, right? So that's an important distinction because we can actually deploy that on premise as well for customers. But it's still as if it was kind of a local cloud for them because they can access it even outside of their company. For example, we have customers using VPNs to access it from home or, or wherever. So it is kind of a local cloud, which is important for collaboration, but still the data is secured on their servers. So you have these kind of aspects that we have to always juggle when we, when we talk with the clients.

Joseph: What are some of the emerging challenges that you're seeing in the engineering design space?

Louise: Well, there are a lot of challenges, I would say. One is what you mentioned before, complexity, right? So things are getting more, more complex and it's more difficult to know exactly all of the parts of your system and how they relate together. And the other parts I would say is regulations, right? So there are more, I mean, technology is usually a bit ahead of regulations, right? So if you think about flying cars, for example, there are already like prototypes that's, that have been shown to, to fly and drive, right? But regulations are a bit behind. So that while the regulations are being worked on, we need to make sure that we can adapt the products that we are building so that they kind of meet those regulations, right? So that, that's the tricky part because it might be that, well, in 2030 there will be this requirement implemented that you need to follow, but you need to make sure that today your design actually is built to be able to meet that requirement, right? So that's, these are the kind of tricky things that I see are coming.

Joseph: So that's, that would be one way in which compliance with international standards influences your, your product development.

Louise: I would say yes and no. So in in the, the value space product, we don't kind of force any standards on the company, right? So it's very, we've taken the, the route of being very agnostic to what kind of product you're building and what kind of industry you regulations you're following. But we have built up this process so that you can actually follow it, right? So imagine that you are in the automotive industry, there are certain regulations, national or international or, or whatever they are, we can make sure that you can import those to your, to your value space software and that you then break down and connect your requirements for your products to those standards, right? So that you can track basically this requirement that says something about the battery system. Does this come from a regulation or does this come from an internal need that we saw where a customer requirements, right? So you can actually break that down then and see the full overview of where those requirements came from from the start. It's, that's the whole idea.

James: With your side of the engineering aspect, is supply chain affecting your company at all in any way?

Louise: I mean, not, not our company directly. Not in the way that we make the software, but it definitely affects our customers, right? So I'm sure there are, it's not something that we are experts on today, right? A lot of our customers actually build, if you think of the, at least the mechanical systems, right? They build them in-house from scratch. So that's, that's one thing. But, but I think there are a lot of things that we can do more for, for the supply chain. Right? It's also about what you said, like predictability, right? Will these parts exist in a few years or like how do you Yeah, it's, it's a whole topic of how you manage the, the supply chain as well.

James: Would your design kind of play into that? So say, say a company had something they knew they couldn't get 'cause of supply chain issues, could you put, put into your assistance something like redesign this aspect because of shortage and, and it would actually plug something else in, in that space that they could use?

Louise: Yeah, that's definitely one of the visions we have. So especially when we go more down the AI routes, right? That the AI would be able to then, or the assistant would be able to then predict where can you have problems in the future and where would you like it is not necessarily doing the work for you or for the engineer, but it's more pointing to where the problems might be, right? And then you still have an engineer taking the decision, okay, maybe that's not the, the most or the, the requirement that we need to, we need to follow. We might change the requirement or we might change the design, right? So then, then it's a decision of the engineer as well to, to help. But definitely we can, I'm saying now here, the vision, right? In the future, help take those decision and help make suggestions even of what could be there instead. Right.

Joseph: Could you tell us a bit about the importance of data integration in modern engineering?

Louise: Yes, that's a, that's a great topic. There is a whole world of different tools, right? And different data and different kinds of data in the engineering space and in, so with valley space, we specialize on, on basically the, the system engineering data. So like requirements system design and, and verification. But it ties very closely to then when you go into more detail design, of course on the, on the Altium side, it ties very much to the, to the bomb and to the parameters of the components that you select, right? And it also ties to the PLM, it also ties to the ERP. So there is a lot of integration needed for this data to be consistent. And that's, that's one of the main things that we want to make sure that the data is consistent, because that's where a lot of problems come, right? So imagine if you're working for four months with certain assumptions and then you figure out that, well, it was actually changed months ago, but I didn't know about it. So one thing is actually making the data consistent and the other thing is actually notifying people when things change along that, that full chain and obviously one tool will not do it all. So we need to have those integrations and make sure that there is a continuity of the data across all of these kind of areas. So it's more difficult than it sounds, but, but it's a topic that is very interesting to, to look into.

James: One, one thing I just wanted to clarify, for people listening who might not know the assistant that you have, is it a standalone offering or is it a plugin that, that operates within other softwares that design engineering?

Louise: So how the assistant works today is that we're using OpenAI. So we're using their large language model to, to process our requests, right? So what happens is that, for example, if you have a requirement and you wanna say, okay, how can I improve these requirements so that it's closer to the, in CSI standards, that's, I know for example, if I, if I want to send this to my customer or supplier, it needs to meet certain standards in how it's written, et cetera, then we take that requirement, we send it to the, to the API of OpenAI, it'll then kind of suggest you an improvement and then send it back and say the, is this better? Do you want to take this requirement or, or not? So in the end, it's still the engineer that decides if they want to go with that suggestion or not. But it basically uses, yeah, it's uses basically the, the chat GPT model to, to get those answers. Okay. We're also working on a, on a model that is not through OpenAI because we know there are some companies that have concerns about sending data there. So we're working on al also a local model that can, can be, Yeah. That, that's, that's not sending the data outside of your environment, basically.

Joseph: Are there any trends you could tell us about for the next generation of engineering tools?

Louise: That's a good question. Well, I think definitely, well, most of the startups that I've seen coming up in the last few years definitely have these cloud aspects, right? So all of them are browser-based and all of them have very much focus on collaboration, right? So it's, I think it's basically, well, it's collaboration and it's user experience, I would say. So I, I think what we're seeing a lot is that people are trying to appeal to different kinds of users, right? So it's not, we're going there, there are still specialized tools, right? But, but if you look at tools like, well, new kinds of pmms or cut tools, right? They are also going to the browser and they are also kinda making sure that each user, whether you're a specialist or whether you're a project manager or whether you're the, the CEO, right? That you can have a different view of the data and understand from your perspective where you are in the project, right? So you might have dashboards that appeal more to the managers that can tell you, well, where are we in the process? Like, how many requirements have you actually verified? How, how, what does that mean for my project timeline? Right? So the, the data is there, but the user experience might be different for different kinds of, of users. Right?

James: I wanted to ask as well about your company joining Altium. That was something that happened. I think it was, was it last year?

Louise: So we were at the, at the stage of our company where we basically, one year ago, a bit more than one year ago, we were contacted by a nun who is the, the, the GM for the cloud part of, of Altium, right? And he said, well, hey, you're doing something interesting. It's, we are interested in the requirements part because at Altium we don't do that yet so much, right? Let's have a talk. So we said, yeah, that, that sounds really, really interesting. It's very cool to be contacted by one of these like bigger organizations that have an interest in what we're doing. So we started collab a collaboration with Altium, right? And it's, it went actually very well. So we started like a POC of an integration between the tools and we actually got a lot of interest from that, from, from potential customers, right? So we, we built this kind of POC where we had a few customers try it out and at some point the conversation started going, well, would it make sense that we do something more together? And me and my co-founder Marco, we had a lot of discussions and the, I would say the reason why we took this decision to, to join Altium is that our visions and our missions are very aligned. So the vision of Altium to actually revolutionize and transform the way that electronics is built and the way electronics is used in, in products is a very appealing vision, right? And is very similar to what we want to do, right? So we, we just want to empower engineers to be able to build better products. And it's, that's basically the reason why we wanted to join Altium and join forces because we also think that we, we are quite a small company, right? And there is only so much you can do if you are, if you are small and joining Altium will basically brings us this, the push that we need to actually to help even more engineers, right? To go from a hundred customers to maybe a thousand or 10,000, right? And that's, that's where we want to be, right. To, to to be part of that journey.

James: So there's something other I would like to ask. As far as the AI space goes, do you think it's becoming something that's somewhat oversaturated or is it still plenty of space for everyone to, to expand at this point?

Louise: I think it depends on the application, right? Okay. I think we see a, I mean, in in general there are a lot of like, well chat bots that you can have for different purposes, right? And that's a, a thing that we've seen a lot also in also in some engineering tools that what, what they are doing is more just trying to take whatever model is available and make like a chat bot that you can ask questions. And I think that that could be useful, right? But I think what's even more useful and what we're trying to achieve is that we're trying to really integrate the capabilities of these kind of models in the workflow of the engineers, right? So it's not gonna be, oh, I have a question to the ai, can I, can I please know, what is the requirement for the mass of the satellite? It's more while you're working, as you said, right? It'll pop up saying, well, did you think about this? Or Wait, if you do this change, these things will change. Are you sure you wanna do that or not? Right? And this will be the, this is the impact of, of what you're doing right now, or predicting the project timeline, right? Or predicting that, well if you do this, you have to then read, run these tests and that will take another two months. Are you sure that's worth the, the time versus versus cost, right? So really integrating the AI into the workflow, I think that's where the real benefit will be for the engineers.

James: Yeah, great. Yeah, it's, it's definitely a couple of areas where I've seen like so many companies competing do the exact same thing. So yeah, I think you're definitely right. It depends on the space where, where innovation still room to grow.

Louise: Exactly. And I think you need some kind of structure to it, right? I think if we, if we started Valley Space with the premise of well, we'll just use AI to help engineers, that wouldn't work because we needed to build up this platform and this tool, right? To have a structure of, well this is a, a data model where you can store requirements and connect them to your design and connect to automatic verifications, right? And once you have that kind of data model and people have actually populated the data, then you can start actually giving context to the AI to say, here is where, where we need help or where we need some suggestions or decision. Yeah, decision help basically.

James: Right? Definitely. I I think it's a, that's point where human interaction is still very much required. I don't think quite there yet where AI can think enough for itself to be fully automated, not just,

James: Well, I think that kind of brings us to the end. So I just wanna say, obviously thank you so much for, for taking the time to chat, but also ask you for, for anyone who would like to check out your product, like see what you're all about, what, what's the best place to do that?

Louise: Sure. You can always go to valley space.com to check out our websites, right? And also, well, once we bring this, we're working right now on the, on the real integration with the Altium 365, right? And once that is out, then we will also send out newsletters and we'll, we'll contact our customers to try that out. And that's a really exciting step because that will be the first time we actually have requirements and system design as a native app on the A 365 platform, right? So it'll connect very tightly with the electronics design and with the, with the schematics and with the, with the PCB design as well.

James: Exciting and far as far as keeping up with sort of announcements, that sort of thing. What social media should people be following?

Louise: Well, you should follow us on LinkedIn. You should follow us on Twitter. And we're not that active on Facebook anymore. I think we kind of abandon that now, but, but on LinkedIn we have a lot of updates. So I think that's, if you follow Valley Space on LinkedIn, you'll get, you'll get all of the updates you need.

James: Fantastic. Well, again, thank you so much for coming on the show and it was, it was great chatting with you.

Louise: Yeah, thank you. I'm very excited for the next steps in bringing this two engineers together with Altium. So thanks for having me.

James: Anytime. And for anyone listening, come back next week and we will have another guest for you.