Transcript
Speaker: Hello and welcome to Edison TV. Today I'm speaking to Tom Clayton, CEO and Dad Khan, CFO of IntelliAM, the artificial driven industrial analytics company that focuses on improving reliability, uptime time and productivity in manufacturing environments. The company has just raised 6.3 million of equity funding to accelerate growth and in parallel with that announced an uplist from Acquis to AIM.
Speaker: A half a million retail offer is currently ongoing via the BookBuilt platform. Tom, many thanks for joining me today. Hi Dan, good to be with you. And can you start by reintroducing the business for investors? you know What does Intelliam do and what problems does it solve for for manufacturers?
Speaker: Yeah, I mean, ultimately, the Intelliam AI platform is about getting more for less, which is what industrial AI should be about, is the true productivity conundrum.
Speaker: So essentially we we we connect to the machines of the factories, the assets of the factories and provide a great deal of intelligence, but it goes right through to the supply chain of the organization. so Essentially, we are creating, we're taking huge amounts of data, ah over 16 billion data points a week are now being ingested.
Speaker: And from that, we're creating insights that are providing reliability intelligence in terms of safeguarding and providing mitigation and and around processes and machinery.
Speaker: But also we're providing productivity and operational insights where we are essentially getting greater throughput efficiencies, reducing waste stream efficiencies.
Speaker: And so the decision logic right through to the planning um and the organization of of these businesses means that they can lower their cost base at the same time as increasing their throughput. That's essentially what we're providing.
Speaker: Thanks. And you work with some fantastic companies. Can you first sort of talk about the types of companies you do work with? And then also um talk us through a customer example, you know, what is the return on investment? How quickly can customers get a return on investment from using your your technology?
Speaker: Yeah, sure. So, the I mean, we've we've we've got a real strong presence in the food and beverage industry. So we're serving roughly 20% of the world's top 100 food and beverage organizations and beginning to so to sort of expand across the estates of these organizations as well.
Speaker: um So that that's probably where we're most predominant. However, we have had quite a... and moving to the sort of building materials market, ah pharma and chemical processing are also quite prevalent. So the, you know, the industry is quite, the or the verticals that we can reach are quite wide. We're arguably um solving the more complicated problem in the intricacies of of packing and wrapping environments, which is easier to apply to sort of process environments.
Speaker: ah So they're the sort of customers we've got. um And it includes many of what people buy on a supermarket shelf through FMCG. We will be supporting their applications and their processes.
Speaker: um So, I mean, a typical example, I mean, Muller has been somebody who's been cited as quite a big customer of ours. They serve, they they provide the significant share of the the UK milk to the UK market across numerous factories and production lines.
Speaker: ah The typical journey would be through various layers of our organization. So the first layer is about providing reliability and intelligence. So the platform is extremely agnostic. So it doesn't really matter about the age, ah the OEM profile, the machine profile, the sensor profile. We're able to connect to those in quite an intelligent way through a unified way that allows us to add context at speed.
Speaker: And that enables us to at first first and foremost provide a ah more advanced predictive maintenance solution ah from ah from from an engineering perspective.
Speaker: And that can be done quite quickly. That can be ah from a point of order. Within two or three weeks, we can have that established with machine learning algorithms and guard railed large language models plumbed into their factories to provide provide data.
Speaker: and ah And the reason I say that is, you know, we we don't have an AI platform that hallucinates and tries to please people. It's dead accurate. It has to be. You know, this is health and safety. This is where millions of pounds and decisions have been made and we need to get that right.
Speaker: The second layer is where we're taking vastly vastly more data ah from things like the line controls of these organizations, and we're enriching that data with things like criticality assessments, plant maintenance instructions and operational instructions and ah shift patterns and skew patterns and things like that. So this allows them to have co-pilots to create transformational change where they can sort of see right through to the buying where to get ingredients from and the effects on the plan, where where there's particular issues between shifts, how to understand the optimum run speed efficiencies or tolerance settings to maximize throughput, all these types of things. That's generally a sort of two to three month onboarding process to go from from that.
Speaker: And at that point there, we can connect more into what we call agentic AI in the sense that we have closed loop systems. So I think we announced um roughly about 12 months ago, actually, a partnership with SKF, which is the world's largest bearing lubrication system supplier.
Speaker: So essentially you've got Intellium inside. So they that's that's the hardware that they would provide. Our intelligence sits inside there that now enables the hardware to interact with the machine in the environment, maximize the dosing efficiencies and things like that in a closed loop manner. So, you know, there's essentially three areas of AI is machine learning, which is the primary point because the large language models right through to agentic functions as well.
Speaker: Thanks. And actually we published a video with SKF and a number of your other customers talking very powerfully about the return on investment of your product. So we'll we'll post that in the link and with with this interview. um So you talked a little bit about your core machine learning technology there.
Speaker: How is that differentiated from other industrial software companies? And then you've also recently launched the Gentic AI capabilities. Can you talk ah a little bit about but what that adds to the equation?
Speaker: Yeah, it's an interesting one. So the difference ultimately is we're not a current incumbent. So we've come to this market ah with a huge amount of domain expertise, right? We've come from the manufacturing sector with automation capability, asset management capability and and reliability and applied science, et cetera, within our organization. So One of the major steps forward we have over other software companies is we understand the marketplace implicitly. you know We didn't understand exactly what data needs to be ingested, what the correlation is, what the requirements, what the insights need to be, how people need to receive it and interact with it within their own workflow features. So we have all that information kept within the organization and that gives us a massive leg over other software businesses.
Speaker: But the other area is when we are totally, as I mentioned previously, totally agnostic in every way. well If you're a manufacturer, and we most often now speak to C-suite individuals around the buying of of some of the transformational intelligence that we can provide,
Speaker: What they don't want is 50 intelligent islands with a different commercial agenda over their platform. Our platform is totally holistic. It sits over the line controls. It sits over whoever's sensor data is out there and provides a one single source of truth that people can interact with.
Speaker: And a lot of that has been done by, we we did a big launch on the stock market about three months ago, actually. And we talked about cracking the code of industrial performance. And it's the way that we unify that data, or land that data through our intelligent namespace organization.
Speaker: It allows us to provide really intelligent solutions. And I think we genuinely have a ah first mover advantage. and and the and And the list and the raise right now gives us, obviously, ah a great deal of of wind beneath our sails. So it's a super exciting time to really start to scale out because we can do that at speed now. And that's the real key to this.
Speaker: And i mean your your recent customer momentum looks to be good. You've you've recently won new business with Mars, partnership with Sky.io and also a large industrial customer agricultural customer. story um can you can Can you just talk through those, but also the significance to your to your growth trajectory?
Speaker: Yeah, I think in the first two years of being on the market and the and and moving to like the the move that's taking place now, there's been an awful lot of productization around the platform.
Speaker: And some of those logos that you mentioned and and many others that we could we could talk about have been on that journey. Some of them were early adopters of that organization. What i was just mentioning there and the way that we unify and move now means that we can now move at pace. We can scale at pace across these estates.
Speaker: So I think that's been a major breakthrough. um i mean, if you take somebody like ah a Marshalls organization, we we were connected to sort five five of in fact, six sites quite quickly, you know, ah within weeks. You're connecting and and releasing value to organizations. And that's really quite important.
Speaker: um And that moves us to the Sky.io that you mentioned, because obviously we've set up an office in the U.S., If you look at our portfolio of customers, a large percentage share of them are American-owned businesses. You mentioned the agricultural business, you mentioned Mars, Post Holdings, which is Weetabix in the UK, etc.
Speaker: If we're providing insights and value, then there's a natural evolution that can take place into that market with case study examples within those organizations. and you know It's a huge addressable market.
Speaker: What we decided quite early is what we don't want to do is set up another software business in the US. We want a commercial entity in the US. So what we want is the right integration partners. Sky.io a wonderful company, you know up to 200 automation engineers deployed across the US.
Speaker: And whilst we've productized our platform that largely takes out a lot of the upfront engineering work to make sure that we can scale, ah there's always going to be occasions where, you know, pulling data from different silos, making sure businesses are ready, AI ready, and the piping essentially between the factory and the cloud is essential. And that's the sort of work that Sky.io can provide for us and where we're looking for ah an integration partner in that space. And it allows us essentially to just scale at the rate that we need to.
Speaker: Great. And turning to you, that Dowd, um can you talk us through um how customer relationships develop from initial engineering work through to recurring software subscriptions and and then how that also translates through to revenue growth and and then ultimately towards operational leverage as you as you grow the business?
Speaker: Yeah, sure. i'm so So fundamentally, yeah um our model is a ah land and expand model. So we often begin our customer relationship through established engineering and asset management services.
Speaker: and Now that gives us a deep understanding of their operations, and importantly, it builds trust. and The next step is to connect the manufacturing data into the IntelliAM platform, and that creates this sort of digital foundation for which we can deliver our software and our AI capabilities.
Speaker: Now from that, ah the opportunity is to expand and we may initially connect a number of manufacturing lines at one site, but as a customer sees the value, we can add further lines, additional sites, and potentially add new geographies. and A lot of our customers are international um and each expansion increases subscription ARR and also makes IntelliAM increasingly embedded in the customer operations, which strengthens retention and and long-term value of the relationship.
Speaker: Now, financially, that changes the mix of the business over time um towards sort of higher high levels of recurring software revenue. And we are targeting a minimum sort of 70% gross margin on software subscriptions. And as Tom was mentioning, the platform has been architected for scale using our IntelliAM namespace and a unified namespace approach. Now that means that revenue can grow significantly faster than the underlying cost base.
Speaker: We expect to use AI in tech extensively within our organization and that improves productivity. So we should not need um shouldn't need to increase headcount proportionally with revenue. Now that operating leverage is an important part of our pathway to profitability over the next few years.
Speaker: Thanks. And then now turning towards the fundraising, I guess the use of proceeds, um you know can you can you discuss how that supports your your growth priorities, particularly US expansion, um but but also where you're investing that capital in order to to accelerate that growth?
Speaker: Yeah, um so the proposed sort of AIM move um and the fundraising is about giving us capital um and the platform to accelerate the model and um and that we you know with the but that platform that we believe is really scalable. So AIM gives IntelliAM access to a broader institutional and growth investor audience.
Speaker: while also the fundraiser allows us to invest selectively behind some of the very large addressable markets. And in the US is the obvious example there. and We don't believe we need to replicate and a large infrastructure base um in the US as we have done in the UK. The product is designed to scale internationally and to scale across across real estate. so What we need initially is a relatively small number of the right people on the ground, supported by targeted marketing and business development investment. to build the pipeline and convert opportunities.
Speaker: Now for investors, I think there are a few clear milestones over the next few years. The most important is the growth in ARR. um Alongside that, investors to look for the evidence of the land and expand model working, so increasing between sites within our existing customers, and also and sort of adding adding new logos, you know, initially from a a single site and then sort of expanding across, again, sort of regional and international locations.
Speaker: So ultimately the strongest validation of the model will be a combination of the ARR growth and the increasing penetration within existing customers with also new customer wins and improving operating leverage within within the financials.
Speaker: So if we continue to growing recurring revenue while costs increase a materially slower rate and that and that will progressively move us towards profitability. Perfect.
Speaker: Tom, Dowd, great to catch up. Many thanks for joining me today.
Speaker: you
