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This transcript has been lightly edited for length and clarity.

When I think about the adaptation problem that we're trying to solve with Orbital Century, the challenge that really comes to mind is a knowledge gap — and it’s a specific knowledge gap around time and understanding datasets and time series in real time.

There’s gaps. We have lots of data points from many of the phenomenal tools that have been developed in the remote sensing space, from low Earth orbit satellites, to in-ground sensors. But a sort of comprehensive, large geographic continuous view of the world is something that does not commercially exist.

And that's what we want to bring to the table by developing a geosynchronous satellite that we’ll put up in orbit. A geosynchronous satellite rotates at the same speed as the planet orbits, which has the effect of sort of having it hold still over a very large region. This allows us to create a live stream of data.

And the first challenge that we want to take on with this is tracking and monitoring wildfire in real time so that we can provide data back to the folks that need it — like first responders — in 15 second increments so that they can see how a fire is moving in real time.

That’s the problem we're trying to solve right in front of us in the short term, and we also anticipate in the medium and long term addressing other perils and other challenges with that same technology.

In terms of wildfire right now — climate change is definitely driving more impactful wildfires. We are seeing now in the summer of 2026 warm and dry conditions leading to increased wildfires in many places. Some places prone to wildfire — like Canada - and other places significantly less prone.

I’m currently in the UK, and there are wildfires in Wales and Scotland, which is a bit wild! So we only anticipate this getting worse with unchecked climate change and it needs to be something that we're going to have to adapt to and learn how to prepare for.

So wildfire is going to have to be something that communities who are not typically used to it learn to live with and adapt to. I will not claim that we will solve all the world’s problems with our satellite solution, but we hope to be a part of the broader solution set and to provide some of the data and knowledge that folks need to prepare for and adapt to these challenging situations that we’re going to be finding ourselves in the years ahead.


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 I have a co-founder named Mark, and we are [putting in place] a fantastic team to bring this together. Mark’s background is in building satellites for the intelligence community and then for Planet Labs. So he's actually built and launched satellites to solve real problems — which is fantastic.

My background is where space meets insurance. I spent a number of years at NASA. I spent a number of years at RMS, in the catastrophe modeling space. I spent some time at Cape Analytics, doing computer vision on aerial data and bringing that to market. And I think those two backgrounds and experiences coming together help us understand how we can actually bring an impactful commercial solution to the space.

So Mark brings that technical expertise and background, and I’ve actually been in that enterprise business space, know what the problems are, and know how we can bring a solution to bear that will actually be useful and impactful.

In real time, we hope that we identify fires faster and are able to monitor them, and therefore allow first responders and people impacted to react better and hopefully lead to saving lives, property, and ecosystems. That alone is a very big goal: fire management.

Then the other piece is that once you have a dataset that allows you to sort of play back how an event unfolded in real time, then you start to be able to do some really interesting things in the cat modeling space. So you could look back and see how the fire progressed and then compare it to your models and say: “Hey, was my model accurate? Did it go in the right direction? If we considered this wind speed and this topology and things like that, what happened?” and “Do I need to update my model?"

Then with better models, hopefully we can improve outcomes moving forward. I'm also personally hopeful that having the data be played back in real time will help us understand even more which mitigations really matter for communities. We have a great understanding of that right now, but if we can take it multiple steps further and really provide people with clear [information on what] worked and what didn’t, that will encourage communities and individuals to take the right steps to keep themselves and their property safe.

Our customers are insurers and utilities to begin with. We also have a dual-use capability, meaning we have a defense application separate from the wildfire application [so our other customers are] defense organizations.

I have not spoken to anyone yet who says: “I don’t need a continuous data set." More likely there’s occasional pushback around whether this should be commercially provided or [provided through] public organizations — which is a fair and valid question. I will always be here to say that organizations like NASA and NOAA and ESA are incredibly important.

The work they do is foundational to everything that we do and really needed for validation and verification. But also they are solving for broad public science [cases], and we are trying to solve these specifically commercial challenges.

There’s another piece to that too, where we’re explicitly not charging first responders for some of the critical data. Our customers seem to understand that if we give first responders the data, they — utilities, and insurers — benefit because loss is reduced.

If first responders have better data, they can respond better, and then property and lives are saved. [This is good for utilities too because] public pushback is less if fires are put out faster.

It’s definitely explaining the livestream from space capability over a very large area. Depending on my audience, some folks who are more familiar with satellite data might be like: “Well hey, the data I’m familiar with comes in these narrow strips, and it’s just a flyby, and I can only get an image, and it’s maybe at best every 30 minutes that it gets updated — so what's [different with you approach?]” And then we have to explain about geosynchronous data and how a geosynchronous satellite is further out from the planet and rotates at the same speed as the planet and therefore kind of holds still over a region, and that covers a huge area, like the entire Western Seaboard of the US, and then can always be on, always providing data — like a continuous stare.

That’s one way we explain it. If they’re even less interested in orbital mechanics and are not familiar with satellite data, another way I like to explain it is it’s sort of like a video doorbell from space — like your video doorbell is always on and alert for something coming by, somebody ringing the doorbell, somebody dropping a package off.

This is the same thing. [Our satellite] would alert up to say: “Oh, hey, we spotted a hotspot. It might be a fire.” Thirty seconds later: “Okay, we’ve confirmed it’s a fire." Five minutes later, "Okay, we see how the fire’s progressing, and here’s up-to-date data on that every 15 seconds.” That one seems to go over pretty well — people seem to understand that conceptually.

Boy, is it hard to raise money when you are not an AI company in 2026!

I would say we went into this believing obviously this is a good idea, and while we didn’t expect people to throw money at us, [we thought] once we explain it a few times, people will come around.

By and large, people were like: “This is cool. This would be needed.” But we ran into a lot of headwinds with being a deep tech, hard tech company looking for funders in today’s AI environment when there's so many AI tools out there competing for funds.

But we were really lucky — I think because the idea is very sound — that we have got some really awesome funders behind us who get it. So I think the biggest challenge is it took longer than we expected, and we had to really look for the right kinds of funders who really understood the space, the challenges, but also the possibilities.

Once we unlocked the right folks to talk to, [fundraising] went really well. But there was a moment, probably in the early spring, where Mark and I were like: “Gosh, are we ever going to be able to convince anyone?” It’s so obvious this is such a good idea. We really need this. You can see it all around us with climate change — it’s so important.

There was definitely a month or so where we were like: “Can we do it?”, and I’m glad we stuck it out because I’m really excited about where we are now.

For me, coming from the commercial enterprise sales space, a thing I learned was how I talk to our prospective customers and how I talk to prospective funders are very different.

The customers want the brass tacks, and how is this really going to work, and how can I really use this, and how am I going to take all this data and do anything with it?

The VCs really want vision. That’s cool — I get why they want vision. But how we speak to the folks that really want to see the vision — and what we think is possible and how big we think it could be and how kind of game-changing it could be — is a very different conversation than talking to an enterprise customer about like: “Hey, here’s the specific problem I solve for you tomorrow.”

So learning to use different talk tracks between the people who provide the funding and the people who are your customers, and getting really good at that, was a big learning, that I would promote to other founders in this space.

It seems sort of obvious, but took us a little bit to fully understand that and use that when applying for funds. 

My personal perspective is that there is a lot of capital flowing into AI and software-type solutions. There’s some value and interest there, but I definitely think it’s sort of over-egged a little bit.

There needs to be more capital put into tangible solutions, hard tech, deep tech — material things that solve real problems: batteries, and new types of air conditioners, new chemical processes, biological solutions and things of that nature, that is where it’s really critical to be thinking about putting funding.

I understand those don’t have quick returns on investment, but that’s what’s going to move the needle in the years ahead — those types of solutions and not 10,000 AI solutions, which will probably eventually all be aggregated up into a few core solutions anyways.

The other piece is: which markets are you selling into and [who are you] working with? We’ve talked to investors who are like: “Oh, insurance, utilities, those are hard.” I’m like: “They’re hard, but they are at the front lines of this problem.” They are the ones dealing with the impact and fallout of climate change right now, and therefore they are going to be the ones who heavily influence the direction and impact [of our response].

They’re the ones we have to sell into to really make a difference here. There are actually some AI solutions that can sell into this space, but I see folks sort of shying away because it’s hard — and I don’t think they should. I think they should be working with these folks, because they’re at the front lines, and that’s how we’re really going to drive change.

Climate adaptation is a team sport, and we all need to approach it like a team sport. Even specifically with what we’re trying to do at Orbital Sentry, we are a commercial entity, but we recognize we stand on the backs of years of public programs that have gone before.

We need those public programs to continue to validate what we’re doing and to progress the science. We need industry to get on board and not just wait for government to solve all these problems, but to be a part of the conversation. We of course need communities to support adaptation measures and to work with us.

We want academics to validate our [Orbital Sentry] data and to use it to do cool science, and we want commercial entities to pay for our data to help solve their commercial problems — and we hope first responders use it to put out fires faster. And this makes a bigger, more complicated network that we have to work within and operate within, but I think we have to, and I think that’s just the way of it.

I was at a climate conference a few months ago where there were utilities and insurers on the stage together talking about wildfire, and folks were commenting like: “Oh, you don’t typically see these two industries together talking about stuff." But they should be! They both face this problem. They're both at the front lines. There’s absolutely tons of knowledge and interesting things they can share. Obviously they are starting to and that's great — and we really hope to be a part of progressing those conversations, being a part of those forums where we do start to collaborate and work across industries, work across academia, work across government, et cetera, to really solve this hard problem facing everyone.

What other climate adaptation use-cases could geosynchronous satellites solve for?

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Thanks for reading!

Will Everill & Louie Woodall
Editor, The Adapt | Editor, Climate Proof