Implementing New Technologies - Part Four - With Florian Beil

Welcome to the Trend Detection podcast, powered by Senseye, an industry leader in using AI to drive scalable and sustainable asset performance and reliability. This is a new publication designed to help you go away with ideas on how to achieve maintenance efficiencies.


For this 4-part series, I’m joined by Florian Beil, CEO at Axulus Reply, an accelerator to enable manufacturers to embrace the Industrial Internet of Things.

In the fourth and final episode of this series, we discuss what the current demand is for predictive maintenance technologies and what the future of the industrial internet of things looks like.

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Key topics covered (click to jump to the section)

  1. The challenges with the integration
  2. The demand for predictive maintenance technologies
  3. Key themes over the next 10 years 
  4. Key takeaways

Niall Sullivan, Senseye: Welcome to the Trend Detection podcast, powered by Senseye, an industry leader using AI to drive scalable and sustainable asset performance and reliability. For this third part series, I'm joined by Florian Beil, CEO at Axulus, an accelerator to enable manufacturers to embrace the industrial internet of things.

In the fourth and final episode of this series, we discuss what the current demand is for predictive maintenance technologies and what the future of the industrial internet of things looks like. I hope you enjoy it.

Yeah, and it's good I guess to have different focuses for different personas. Sorry, stakeholders, not... I'm speaking marketing speak now. But different stakeholders have different objectives and different... They're not as interested in something that say the maintenance or engineers would be interested in. But yeah, so that's interesting.

Florian Beil, Axulus: Right, Right. 

Niall Sullivan, Senseye: I wanted to just briefly bring back the integration. Obviously a key part of your work is integrating systems and processes, so how important is that in order to deliver a successful project and then scaling beyond that. So we've talked about some of the challenges before, but it might be good to sort of dive into this again a bit more.

Florian Beil, Axulus: Yeah, I think look, the integration of systems and processes, given the realities in industry is a key part. And I think the main changes though, which hit now, or which are interesting maybe, is that so far in previous decades, I mean there is a whole industry around delivering projects that connect software A to software B. And this was a system integration industry, so there are a lot of system integrators out there which can connect anything to everything. And do that as a project, as a time [inaudible 00:02:10] base.

Now I think that there's a lot of innovation now also coming up in that field, because actually based on the technology we have today, which is all microservice based, API defined interfaces, which you can connect. It's again a solvable issue of mapping APIs to each other and making that in a way that you can configure the connection. And which is, to be honest, if you look at our sales pitch, there's one key slide where we say, Axulus is based on legal world assumption. So today technologies and solutions are not monolithic anymore, but they are built out of building blocks which fit together and managing these integrations is possible at scale.

So what I would say is, yeah, it's highly important, but I also see some interesting technologies coming up there. And this goes even down to business software. I don't know if you've heard about Sapphire. So it's a cloud based subscription software tool which does nothing else than mapping APIs to one each other. And I have a graphical user interface where I can configure. So for example, if my CRM system does this and take this information and forward it into my analytics software like [inaudible 00:03:32] for example. And this basically fully addresses this whole system integration work, which was done as projects as a product, which I find pretty interesting. And there are a lot of technologies like MuleSoft for example, which are going more into industrial space.

But what I'm saying is that these type of solutions also Axulus, try to really productize this project business, which it was before, into a more scalable integration connectivity type of solution. And I'm a hundred percent sure that also the system integration world will change quite a bit with these new technologies coming up. Because if it's easy configurable to really do an integration, I don't need a project for that. I can use a template from Axulus or I can use a Sapphire integration, SAP they call it, I think to connect all the different things which I have. Which then again, on the other hand of course puts the software providers on the pressure to provide these APIs and provide these connections.

But I'm a hundred percent sure that this is the future. If I would be a customer, I would not accept a monolithic EOP system anymore where I need to buy the whole thing. I can only customize it with R&D development work or worst case I even need to pay for API calls which I receive. So I think this is all changing now based on the technologies and which is again, on the other hand a very good news for us or also for Senseye because it makes your technology much more valuable if it's easy to integrate it into a, for example, I mean Senseye into CMS, computer maintenance management system. Without that the customer needs to spend half a million for a team of five people for half a year, and you just configure it. So I think long answer short, it's very important and there's a lot of technology coming up and making this much more scalable, which will help us and the customers a lot.

Niall Sullivan, Senseye: And I guess certainly from your point view, I feel you might agree that a lot more go to market motions will involve... It won't be just... And we find that already, because our partner network is a very important part of our go to market strategy. But there'll be a lot more partnerships let's say between different software providers and they'll go to market together as partners rather than Senseye just turning up and saying this is us. It's really a bit... And I mean at that point you can say, Oh we can integrate easily, open our APIs, that kind of thing. But it's probably much more compelling if you come together with a full, let's say complete stack, is that the right term? Maybe, I don't know. Offering to the market team. So you don't need to go out looking for this part or this part because we've got it all. So that could be the future of SaaS product I guess in general when selling.

Florian Beil, Axulus: Yeah, I think so too. I think I fully agree with that now. And at the end of the day, I mean what I learned, I guess was one of the... Actually, I mean the real aha moment I had for Axulus was when I sat in a meeting in one large German automotive OEM where we tried to again position IOT platforms and solutions and there was the plant manager or the line manager coming in said, "Look, I don't have time for these workshops. What I need is our templates which make the entry barrier for my team from problem to installed, up and running as small as possible. I don't need workshops, I don't need Excel, I don't need brainstorming. I need a template where I know it works and where I can click and deploy." I mean ideal worlds, "So that it's really very slim effort required or as little as possible so that I can use it."

And I think this is where a lot of the thinking and technology at the moment goes into. It's not so much about... Also going into, let's call it this way. I mean, there is of course a lot of new technology coming up. I don't know sensors. Quantum computing, whatever. So small things that smart technology which can do crazy and fantastic things. But I think on the other side there's also a lot of innovation going into the way how you adapt and use that technology which is maybe even equally if not more important. And things like Sapphire, things like MuleSoft and also I would maybe list Axulus there are technologies which are designed to address the meter problem of adopting digital rather than adding the next cool feature onto something. Because if the barrier, if the distance for the end users too far, they just won't use it.

Or understandably they need to reduce cost so what should they do? They cannot spend a month or so trying to design a UI or design a stack and enable that. It needs to be a product. And I think that's why your question was so important there just to really see there needs to be also an effort in innovation and there will be an effort in innovation.

And I think personally that this will again accelerate the adoption of digital quite a bit and will make the collaboration also much easier because then if this is the case, if it's easy to integrate, easy to use templates and a lot of things which are cumbersome today like collaboration between different software parts or jointly meeting up to try to explain in a team of 10 to one customer what the overall stack is looking like, this becomes much more easier.

So it's helping all of us, and I'm really counting on that with this system based support, this whole partnership thing jointly bringing together the best technology to solve a problem is much easier and much more scalable. And I'm actually looking forward to that a lot because I spend too much time in maybe brainstorming meetings where I just wanted to go there and say "Hey, we have a [inaudible 00:09:59], this is my part and it works together and Senseye we have lot of partners coming together. It's one template, you can use it right away, don't waste too much time." That's what I'm striving for and I think this will be the future for sure.

Niall Sullivan, Senseye: Yeah, that must be music to the ears of those people because the complexities of some of these projects or what they think of at the start of the project that solves a lot. And I guess at the end of the day the overriding theme is it's best for the customer, it's the best route for the customer to team up together rather than try and make your own way in. It just doesn't help anyone, just slows things down and causes bumps in the road in the projects.

I just wanted to... So we got a couple of questions left I wanted to dive into and I wanted to first of all focus a little bit more... Took quite a long time, sort of flying past really actually I'd like to say. Well I'd like to think it has. But what I wanted-

...Say first is, and you've very [inaudible 00:11:00] mentioned it a few times in your examples, but in general, how much demand are you seeing for predictive maintenance technologies at the minute?

Florian Beil, Axulus: Look, I think the whole thing on predictive maintenance, there has been in some... I don't know exactly why to be honest. I think this was the first most natural application of AI in industry. So if something could tell me when assets presumably will fail. So there was already quite some development there I think. But I think where I see still a lot of market is... So it's one thing of the concept of predictive maintenance and saying Hey in principle, we can now connect this asset and predict. It's a different thing on having an end to end view. Like okay, I still can connect an AI, I can click something but forwarded information into CMS, enabling the teams to do a better maintenance process, conserving the information in a system which my experts have, which always worked with that pump and no executive phase.

So there's I think a core technology point where there was a lot of development but it is not necessarily immediately adaptable for all the customers. I think that the end to end adoption of the whole chain from the bite to the maintenance guy doing a better job or enabling him to do a better job, I think that's where there's still a lot of demand. And of course if you have a scalable approach like also Samsung has, so if I was to use technology correctly, it's one of the innovation parts is that it ought to generate a fingerprint of an asset it ought to learn, so okay, this is now deviating from it. So again you are working on a technology which really reduces the entry barrier for predictive maintenance a lot compared to previous projects where you need to define a metering concept, you need to collect the data, you need to integrate and normalize it. There's a lot of effort to get one thing done whereas you are providing a technology which is really scalable and to some extent plug and play.

And I think for these type of solutions and predictive maintenance, there's still a huge space because so far a lot of the predictive maintenance business cases were rather hampered by the effort required to get it up and running. So of course you could save some money with an old style predictive maintenance solution. But of course if the effort overcome your savings off for 10 years by I don't know, factor of five, nobody would do it. So that means the easier you make it for a technology like predictive maintenance to be adopted, the more it will spread naturally. And I think that is where there's still lot of potential.

And I know there have been a lot of discussions in predictive maintenance around, so what is a real business case if I go to India because there's a person which I can put right beside the pump and listen to it or it's not expensive enough so I can have a replacement [inaudible 00:14:14] on. That is of course all potentially true, but I mean this all changes of course the easier it is to adopt the technology of predictive maintenance. So if it's just, I would say a connected asset and then I start then let your AI do the rest, it's a different story than if I need to do a six months project on it. So there I see a huge, still a benefit and a demand.

And the second aspect where I would also not underestimate is so far predictive maintenance, at least, I mean based on the discussions that I have heard with my customers is always very, I would say localized asset focused. So I have a certain type of machine and it kind of fails. So how do I measure it? I mean the real scale of predictive maintenance because it's data driven AI comes into play if there's a player like Senseye who has connected not only one asset but 10, 100, thousands and of course with that information you can much better scale the quality of your AI which allows you to do even better service doing better predictions.

And it's, I would say, a self reinforcing circle. So the more you have, the easier it is to connect, the more data you have, the better your AI gets, the more attractive it is again to connect more and then it starts to scale. And I think this perspective of predictive maintenance is not only to be seen on one individual asset level but on a fleet of assets which you can serve. And because you have done a scaling effect in the quality of the service, that's something where I see a huge demand also. And so I still see that as a key element of any digital transformation curve to do predictions on asset stages, asset failures and maybe other adjacent predictive things. But I still see that still after some technology development they've seen there, there's still a lot room to improve and to grow further.

Niall Sullivan, Senseye: Absolutely. No, really interesting to hear your insight on that. And I just wanted to just finish on one last question and it's sort of a look into the crystal ball type moment, but with... Bring it back. Weren't we about to industry 4.0 or industry 5.0 but industrial IOT instead, another term we haven't really linked very closely. But what do you see the future being, and you maybe mentioned augmented reality and things like that. Not that I want to put words in your mouth, but what would you think are the key themes over the next five, 10 years as you see it now. Things change so quickly. As we know. With the caveat of that.

Florian Beil, Axulus: Yeah, I think it's an interesting question. and look, any answer I give you will be of course wrong. But I think based on my gut feeling and what I see in the market, I think the next five to 10 years we'll see a lot more adoption of basic IOT and digital technologies is still in production. So I think that we by far have not reached yet full potential there and a lot of customers will start to adopt, start to scale solutions and technologies like Senseye, like Axulus, like LSR designed to make it happen.

Then of course on the technology side, so if you only talk about the building blocks which are available, there will be, I think what we see now really emerging is, and I was really impressed by what is happened there over the last two, three years is really by computer vision based AI. And of course this was always there, but I think we are now getting into a regime where camera based AI can solve problems which previously needed to be solved differently. So I think that will be a strong component.

One topic I also continuously start to think about is, I mean maybe a little bit far away but still emerging on the horizon is things like quantum computing for very specific problems which cannot be addressed by classical computers. But of course also when you mention it, the convergence of real and digital worlds might be called AR or maybe even virtual reality. My play role, I'm not sure to [inaudible 00:19:05] extends it will change production, but for sure there are use cases that benefit from these type of technologies.

And of course I think I mentioned is computer vision, but I mean A general artificial intelligence topic is for me also a very big topic which will definitely drive a lot of change over the next five to 10 years. I mean I always refer to use cases, so what problems you can solve. But with these technologies like AI, maybe to start even with at the moment, data connectivity, augmented reality, virtual reality, I mean these are again new tools you have in your toolbox which allow again to address the next class of complex production challenges.

And the last thing I would like to mention is, and I'm maybe a little bit brave in saying it. So what I also see is really an acceleration of innovation coming up from very specific but agile, intelligent, smaller companies versus large product lines from industrials. And this is also related to the fact that today when you start a tech company, a startup, you basically have all the tools which previously were only accessible to large industrials. So you have the tools now available for startups. I mean for example on sales side, I mean of course an industrial company like GE or any of these, they have huge sales setups. But what is that worth if today I can't subscribe to zoom in for where I have more intent and more context than anybody else on the planet for 15,000 euro a year.

And I think this is also not to be forgotten, it's not about only the technology in the shop floor, it's also about the business software technologies which allows companies like yours or mine to be very innovative at scale very fast. And I think this will also accelerate over the next five to 10 years, bringing up more ideas, more challenges, and of course there will be a lot of partnering required and networking required, but I think this will become more agile too from that perspective.

So yeah, to the overall, look, I'm very optimistic. I know we haven't had the best two years recently or we don't maybe have the best year this year, but there's still a lot of things which make me optimistic on the technology side, on the customer adoption side because there's a lot of innovation going into, but also on the ability and the agility of new ideas, new companies trying that. So that will be my guess, a little bit broad, but I think we both are in the right field now. So I would not be to worried about the future.

Niall Sullivan, Senseye: Yeah, I think all we know is... Well, after the last few years it's very difficult to... Seems strange to make predictions because anything can happen it seems, but I think one thing is true and is clear that these technologies can become more important, well they are now already, but even more embedded and in a lot of processes we don't even think about day to day I guess as well. So just to finish really, so it's been a really interesting conversation. Really, really. I've learned a lot from it. But just to finish Florian, it'd be really good just to get, say, a few key takeaways for our audience on how to sort get started and then just a short description how they can find out more about Axulus as well. That'd be really good.

Florian Beil, Axulus: Brilliant. Yeah. No, look, the only advice I can give to your audience, and I really appreciate the audience listening in, is to really embrace the technologies which are coming up. And so don't be afraid, it's offering more opportunities for sure than challenges and also embrace new technologies which are targeting a fast and easy adoption of digital, like Exelus, like other technologies which are out in the market. So we really try to innovate to make it easy for customers and end users to use these technologies. And it's also, as it is easy to come up with a use case and configure it, it's also easy to start small, which maybe is also an important message. Don't try to boil the ocean at the beginning. Don't try to end to end digitalize every plant. Start small, start with a use case, use a template, scale it up and if it works then scale it rather than doing a big digitalization approach.

I think this would be some key takeaways, maybe. If That's resonating I would be very happy. You can find out much more. Of course you can contact me personally on LinkedIn or one of my team. You can visit our website, which is where you can look on the videos, you can see demos, you can see templates, you can see our team, you can contact us and of course you can always write also an email to either or to So I think these are the main channels and of course we'll be happy if anybody has a question come up with. And we are always happy to support or discuss further. So thank you for that opportunity now, first of all, thanks.

Niall Sullivan, Senseye:
No, thank you. Cause it really has been fantastic. And so yeah, so that's all that's left to say really. Thank you for a really in depth conversation and yeah, see you next time.

Florian Beil, Axulus: Yeah, thanks very much. I'm looking forward the next time maybe on our podcast now, right? The other round.

Niall Sullivan, Senseye: Exactly, exactly. That'd be great. And talk about industry 5.0 a bit more.

Florian Beil, Axulus: Exactly. Whatever that is.

Niall Sullivan, Senseye: Exactly.

Florian Beil, Axulus: Thank you, Niall. 

Niall Sullivan, Senseye: Thank you, bye bye. 

So that was the fourth and final part of our series, looking at the challenges of implementing industry 4.0 solutions. I hope you enjoyed it. Please subscribe via your favorite podcast provider if you'd like to be notified about future episodes. And it would mean a lot if you'd let us know your feedback by leaving us a review. You could find out more about how Senseye can reduce unplanned downtime and contribute towards improved sustainability within your manufacturing plants by visiting Thanks a lot for listening.

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