Slingshot Aerospace
Geospatial Data for Better Insights

Founded in 2016, Slingshot Aerospace provides cutting-edge insights and data to customers with its data processing platform, using the world’s largest untapped data source—data from satellites in space. Slingshot’s technology goes beyond satellite image processing and uses powerful computing techniques to draw multi-signal predictive insights. In a recent interview with David Godwin, CEO of Slingshot we discuss how the company employs technology that is core to its business in the defense and commercial sectors to drive value and create an impact.

Can you give us insights into the trends in the Data Platform space in relation to your business?

There is an exponential increase in the number of satellites, aircraft, and drones that are imaging the Earth every single day. When dealing with geospatial data at scale, processing is an issue. While certain companies have exhibited the capability of processing this data; it is often manually intensive or one-off projects – with no real repeatable or reliable capability. We are looking to equip our customers with the ability to use this data, at scale, in everyday business.

Satellites are becoming cheaper because the launch costs are going down and more commodity type hardware is being sent into space. There are more standardized platforms, and drones are being commercialized and increasing in scale. All of this is resulting in an overwhelming and increasing amount of data being sent down from the sky and space.

What are the challenges in the geospatial technology space?

It is the ability to manage the massive amounts of data effectively and in turn, being able to harness it to drive true, repeatable and reliable intelligence. A picture is pretty to look at, but it’s the intelligence locked inside it that we are after. Most organizations cannot draw the value out of the data – images or other signals. They might know what to look for, but don’t know how to do it repeatedly, at scale, worldwide.

I think there is a common misconception about a 'one size fits all' approach to managing different types of data. Different organizations have different challenges when it comes to handling and processing the various kinds of data. The imagery, video, and other sensor data that geo-intelligence companies work with it tend to be large-sized files coming in hourly versus the millions of transactions every second or hour that a social media company or a finance company may have to deal with.

The underlying data platforms needed will be different to be able to handle the nuances of each situation.

How does Slingshot Aerospace address these challenges with its solution?

We leverage a mix of big data technology and internal innovations to create our solutions. The platform itself has two aspects that directly and indirectly benefit our customers—the first being; it enables our innovation and R&D team to design solutions faster around customer problems. Through the platform, they get a workbench capability, which can be utilized along with our machine learning (ML) technology to allow our scientists to design solutions faster than our competitors. The second aspect is that our platform allows us to scale the resulting products for our customers in our production environment to quickly deliver consistent, repeatable data sets. Our platform is configured to deal with terabytes and petabytes of data, with each ‘row’ being gigabytes in size—which is not something easy to achieve. When companies engage with Slingshot, they get a partner and a solution backed by our cutting-edge technology. Using our technology, we help them solve the hard problems.

To help readers gain a better understanding of your solution, could you share a case study?

Our data and technology helped the rescue and relief crews of hurricanes Harvey and Irma. Within a day of receiving satellite imagery and other signal data of the affected areas, we were able to turnaround flood maps for rescue and relief workers, enabling them to navigate the challenging situation that was unfolding more efficiently. They were able to get supplies out to people faster and perform rescue operations more quickly because they knew where the open routes were. We also provided coverage of the parking lots that were not underwater so that they could identify staging areas for rescue and relief operations. We were thankful for our close partners: BAE, Team Rubicon, and Planet for working with us on the effort and I am proud of my team for helping save lives that day. For this upcoming hurricane season, we have added damage assessment capability with our infrastructure and debris detection algorithms.

What does the future look like for Slingshot Aerospace?

We have been adding some of the best minds in the geospatial arena to our team this past year, and we will continue to do so in the coming months. We are focused on Defense as a sector but are looking at various other industries to take the technology we’ve built and apply it to enterprise business problems. Building up the platform to add capabilities to our quiver quickly is the name of the game. We are keen on utilizing our algorithms and capabilities in different scenarios, for instance, pipelines, dams, and factories. Over the past quarter, we have been working with signal data like synthetic-aperture radar (SAR) and other sensors that are being sent into orbit for a more comprehensive solution to give us more accuracy and coverage.

Do you have any final thoughts?

We believe the true power of geospatial signal data, at scale, is yet to be discovered. Slingshot partners with its customers to provide long-term, valuable solutions that have a real impact on their business. We start by looking at the high-value problems our customers have, where “eye in the sky” intelligence can help. By taking the right sensors, satellite data, and other data from customers, in addition to our technology and models, we are well-prepped to solve client problems.