Member Spotlight: Ben Pruden

This week I spoke with Ben Pruden, Head of Go-To-Market at Wherobots, the Spatial Intelligence Cloud built by the original creators of Apache Sedona. Ben walked me through how Wherobots is helping climate companies move faster with data, why open source matters, and how his team is reshaping how we understand and interact with data about the physical world. “If you want a concrete visual, Wherobots is a bridge.” A bridge between messy raw spatial data, and the people (scientists, data engineers, developers, agronomists, founders) who actually need to use it.

Watch this video to understand what Wherebots does, and read one!

Daphné Halley: How did you end up working on spatial data and climate?

Ben Pruden: So I’ve always been into data technologies. Even during my MBA at UT Austin, I was organizing a big data symposium with speakers from Google, Apple - all sorts of experts talking about where the data world was going. I knew I wanted to work at a tech company and use data to learn how to tell stories around data products. That led me to Salesforce, where I worked on their analytics tools. From there I went to Elastic, which is all about search, open source, and building data products from text analytics.

And when Wherobots came along, which felt like the next evolution of all that: combining open data architecture, big geospatial challenges, and real-world impact. I care about what’s happening to our planet, and this was a chance to directly support a mission that is making understanding our physical world easier for everyone.

DH: What’s the problem that Wherebots is solving?

BP: The geospatial data world is kind of a mess. There are over 80 different file formats, and most of them are locked into legacy systems that are hard to work with, super siloed, and just not built for the scale or urgency of today’s problems.

What we’re doing at Wherobots is helping move that entire legacy spatial data world into modern data lakehouse architecture. We make it possible to take those fragmented file formats and systems and run them via planetary scale data processing techniques, similar to what you can do with Databricks or Snowflake. So instead of being stuck in old-school GIS software that only runs on your laptop or a single machine, you can build real data pipelines that actually inform things like flood risk, crop yield, wildfire response… You name it.

We don’t generate the satellite data or take the soil samples ourselves. But we help the companies that do make all of that processable at scale.

DH: So how does that apply to 9Zero? Can you give an example of how this helps in the climate space?

BP: Yeah. One we’re really proud of is Overture Maps Foundation. It’s this an incredible nonprofit consortium, Amazon, Microsoft, Esri, TomTom, and others, all building a global, open geospatial map dataset to counterbalance Google’s proprietary tools.

They’re using Apache Sedona, which we created, and they’re now also using Wherobots to modernize  their data pipelines. It’s faster, more cost-effective, and it’s 100% compatible with open source. That data is now powering everything from public-sector applications, to insurance risk analysis, to startups working on climate adaptation.

Another one is Addresscloud, a startup in the UK but scaling internationally that layers flood and fire risk on top of Overture’s maps. Their clients are insurance or real estate companies trying to understand exposure risk of properties. Or Leaf AgriTech. They’re integrating tractor sensor data across all these incompatible APIs so farmers can actually act on what’s happening in their fields. It’s helping people address food security, resource efficiency, and climate resilience.

DH: What’s your role in all of this as Head of Go-to-Market?

BP: Go-to-market is figuring out how to tell the right story, and connect that story to our ICP (ideal customer profile). I help customers understand the value of what we’re building. It’s not enough to say “we process geospatial data.” People want to know what that means for them: Can I model wildfire risk in real time? Can I train my LLM on spatial data? Can I build a better perception layer for autonomous vehicles?

We’re actually starting to work with some early self-driving car companies, because those systems are constantly taking in geospatial data, and trying to interpret it in real time. Right now, a lot of them are using these unsuited or unscalable methods, to model intersections and road features. They need a great deal of precision to ensure the future of self driving vehciles are able to interpret road networks, and what is happening in realtime, in a way that they can respond to based on their algorithms and AI.

With Wherobots, they can build much more accurate spatial representations, faster and at scale, so their vehicles can make better decisions in the real world.

DH: What’s one thing the 9Zero community can do to support you?

BP: I am always interested in collaborating with the 9zero community to create compelling stories about what we are doing with the teams working with data about our planet. This stuff matters, we’re talking about real-world decisions, from crop planning to disaster response to planetary-scale climate models. We want to make it radically easier for the people doing that work to access and use spatial data. So if you have a problem that requires understanding data about our planet, let’s chat, and see how we can work together.