Let’s Talk Future™ - An Oppenheimer Podcast
Feb 26, 2026 · 23 min · 9 segments
The space economy is expanding rapidly, with projectionsrising from approximately $100 billion today to $400 billion over the next decade. Tim Horan speaks with Brian O'Toole of BlackSky and Graeme…
Brian O'TooleGuestGraeme ShawGuestTim HoranHost
I think the geospatial analytics industry historically has been massively fragmented because you require experts across hundreds of different use cases across multiple industries.
And so it's highly manual and it's lacked timely information that would facilitate feed decision-making systems and decision-makers across all of those industries.
The space-based capability tied with communications, with expert-type AI that's delivering insights is the connection, the last-mile connection that's been missing that can defragment the market.
It's As Graham pointed out, it's about delivering actionable intelligence that's accurate, timely, and relevant.
And we have a competitive advantage in that we can collect data hourly in all kinds of environments and different environmental conditions and things like that, that can give us excellent training data to develop very accurate and high performing models from our constellation.
And then when you combine it with other data, you get even more improved performance, which is what the end user needs to rely on.
But we see the practical applications and the impacts that it's going to have across the entire sector.
And so we've built a substantial team of machine learning and data scientists and the tools and processes internally to build and deploy these capabilities at scale.
In other cases, we have a multi-cloud infrastructure that allows us to leverage different cloud environments, dedicated GPU systems and things like that.
We've already done things like put AI on spacecraft so when we collect, we can start detecting things right on the board the satellite.
So there will be a combination over time of more on orbit, but I think the majority of it will be on the ground leveraging applications.
I think the geospatial analytics industry historically has been massively fragmented because you require experts across hundreds of different use cases across multiple industries.
And so it's highly manual and it's lacked timely information that would facilitate feed decision-making systems and decision-makers across all of those industries.
The space-based capability tied with communications, with expert-type AI that's delivering insights is the connection, the last-mile connection that's been missing that can defragment the market.
It's As Graham pointed out, it's about delivering actionable intelligence that's accurate, timely, and relevant.
And we have a competitive advantage in that we can collect data hourly in all kinds of environments and different environmental conditions and things like that, that can give us excellent training data to develop very accurate and high performing models from our constellation.
And then when you combine it with other data, you get even more improved performance, which is what the end user needs to rely on.
But we see the practical applications and the impacts that it's going to have across the entire sector.
And so we've built a substantial team of machine learning and data scientists and the tools and processes internally to build and deploy these capabilities at scale.
In other cases, we have a multi-cloud infrastructure that allows us to leverage different cloud environments, dedicated GPU systems and things like that.
We've already done things like put AI on spacecraft so when we collect, we can start detecting things right on the board the satellite.
So there will be a combination over time of more on orbit, but I think the majority of it will be on the ground leveraging applications.
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