Transcript
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Space based data gathering has been a growing area in the space industry over the last decade. We have an abundance of commercial earth observation companies, for example, gathering tons of data every day. And our guest says turning that data into intelligence is the next logical step. And how does AI fit into this? You knew we were going to ask, right? Well, we're about to find out. This is t minus deep space. I'm maria varmazes. Our guest is Eric Anderson, founder and CEO at synmax. Eric shared why he has jumped from financial market intelligence to space intelligence and what he foresees as the growing potential in the years to come.
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I'm Eric Anderson, I'm the CEO of synmax and one of the founders and I started my career in finance and in trading and and I worked for a hedge fund where essentially my job was as a quant to collect a lot of data and turn that into intelligence. Right. And that's a transformation I think a lot of people don't appreciate. In particular, I think that there has been a growing appreciation for it in the space industry. In the commercial space industry, we recognized that there is more data constantly being created out in the world, especially in commercial satellite industry, and there is a deficit of burying that data into a refined product that is intelligence. What's the difference? I think data holds potential and in the hands of a data scientist or in somebody who understands the data and the problem, that potential can be realized into a customer use case or a solution for a particular problem. Whereas intelligence is the solution. Right? Intelligence is. It is apparently clear that this is the answer to the problem I'm trying to solve. And so that's also Max does, really. And when I was at the fund, we started recognizing that commercial space industry was growing very quickly. And all of these innovative companies like Planet Labs and Blacksky and Satelogic and Umbra and I could go down and down the list that are a part of this new space economy. Launching assets into orbit and collecting data around the globe in a novel way that's not being fully used by the market. And it's certainly not turning into intelligence. And I think that the growing appreciation of data to intelligence is a maturing part of the space industry, because a lot of these companies originally might have discounted that idea. Right. If you go back to the ancient history pitch decks of when they were all raising money and starting up, you'll notice the theme is that they own the entire customer relationship, that they will build the satellite, they'll launch, they won't launch it, they'll have SpaceX launch it, they'll put it in orbit, and then the consumer of it, Right. I'm a farmer, I want a picture of my field. You know, I'm a railway company. I want pictures of my tracks, et cetera, et cetera. Those were the use cases they were thinking of. That makes a lot of logical sense. But I think the industry is starting to appreciate the specialty that is data science and the actual transformation of something into a data intelligence product. So we started Synmax and, you know, we were very early adopters of in particular, commercial satellite imagery. You know, we're great partners with Planet Labs, Black Sky, Ombra, all the ones I mentioned a minute ago, in purchasing their data and finding ways to combine it with a lot of other data sources and intelligence and turn it into a solution that customers can pay for, you know, particularly in the energy space where we do a lot of business, and in the maritime space where we have a product called Via, that is using this novel nascent commercial satellite imagery to monitor the oceans for vessel activity. And this has been a journey of about four years now. And in that time, I think we've found that the correct strategy is to be data agnostic. Right. And that doesn't mean that we don't appreciate that every data source has its nuances that value can be extracted out of, but it is a recognition that the best customer answer is going to come from intelligence fusion, not just from a single data source being Refined into something I was talking about, you know, before we hit record. It's kind of. It's not black and white. You're not, you know, data agnostic or not data agnostic. There's a progression. And part of that is that there are some sensors that are unique enough, right, that you have to build to their uniqueness. But being data source agnostic means that you're not building for the present state of the system, you're building for the future state of the system. And we know that there is a prolific amount of additional investment in the satellite industry. And so we build our system so that they are flexible enough that they can take advantage of the future state of the system when new sensor sets come online, but they're still specialized enough that they can take advantage of the uniqueness of each individual data point.