From the age of seven, my gaze has always been toward the sky. At the time, I lived with my grandparents in Nanyuki, Kenya, where I would watch general aviation airplanes come in for landing. I would point toward the sky and say, “I want to be there.”
More than seven years into the aerospace industry, I now realize that I was searching for the vocabulary to describe a dream I had long before I understood what it meant. I was fascinated by these machines that seemed to defy gravity, and that fascination quietly shaped many of the choices I would make later.
Finding My Path
When I moved to America in middle school, that dream became somewhat less conscious, but it never really disappeared. In high school, I chose to attend an engineering magnet school, where I was introduced to the principles of engineering and began to see what might be possible.
I even tried to take my career in a different direction. For a moment, I thought I would become a chemical engineer. But at the last minute, I changed my major and headed toward aeronautics. I went on to earn my B.S. from Purdue University and M.S. from Stanford University in Aeronautics and Astronautics. I couldn't deny that little girl her dream.
Between my bachelor's and master's degrees, I spent about five years at NASA Johnson Space Center as a Spacecraft Systems Engineer, working on the ISS Internal Vehicle Configuration Team and later on the Gateway Program's Integrated Spacecraft Performance Team.
The Pivot to Data
After my master's, I spent another year stepping back and asking a different question: What problems in aerospace do I actually want to solve?
I explored everything from lunar surface structures to robotics and mission initialization. But I kept coming back to something fundamental: If we want to prepare the space industry for its next era of innovation, we have to think not only about what we put into space, but about the value that space can deliver back to Earth.
That led me to data.
Sensors are becoming more capable. Satellites can capture higher-resolution imagery, wider swaths, more spectral bands, faster revisits, and vastly more information about our planet. At the same time, AI and onboard computing are becoming increasingly capable.
I started to see a possibility: What happens if we don't have to bring all of that data back to Earth before we can turn it into something useful?
Satlyt and the Future of Earth Observation
That realization is what ultimately drew me to Satlyt. We are tackling a problem that I believe will define the next phase of the space industry: enabling software and data processing to happen right in orbit, closer to where the data is actually captured.
To see why this matters so much, let’s look at Earth Observation as an example.
For years, the industry has pushed relentlessly to make sensors better:
- Higher resolution
- Wider swaths
- More spectral bands
- Faster revisit
- Greater collection capacity
The result is extraordinary: we can capture more information about our planet than ever before. But there is a consequence. The traditional Earth Observation value chain assumes that the spacecraft's primary job is to collect data and get it to the ground, where the real processing and analysis begins.
As spacecraft generate more data and customers demand answers faster, that model starts to create friction. Downlink capacity becomes a constraint. Moving everything to the ground takes time. And not every piece of collected data is equally valuable.
Rethinking the Information Pipeline
This opens up a different question: What if the spacecraft could do more than collect data? What if it could help determine what matters?
That doesn't mean moving the entire analytics stack into space. It can start much more simply:
- Calibrating sensor data
- Removing unusable data
- Identifying areas of interest
- Extracting relevant information
- Running lightweight models
- Preparing data so that more sophisticated analysis can happen on the ground
The opportunity is to move the spacecraft from being a data collection point to becoming an active part of the information pipeline. And I believe that shift matters because the Earth Observation market itself is changing.
Customers increasingly care less about simply receiving imagery and more about the insights and decisions that imagery enables. For companies in this space, competitive advantage may come not only from how much data they can collect, but from how quickly and efficiently they can turn that data into something useful.
That is the trajectory I see Satlyt helping enable.
We have spent decades getting better at seeing Earth. The next step is getting better at understanding what we see, before it ever reaches the ground.
So, what happens when the satellite starts thinking? It becomes more than a sensor. It becomes part of the intelligence layer.
And I believe that shift could help push Earth Observation and the broader space economy onto a trajectory that truly defies gravity.
