Terabytes of code, data, and pipelines migrated to Google Cloud and BigQuery in less than three months
10x faster AI model iteration, with 10x more data volume per model
5x more area mapped for soil carbon content
Revenue doubled in first year after migration to Earth Engine
5x revenue increase expected in second year after migration to Earth Engine
By vastly increasing the scope and precision of its soil carbon level maps, Perennial’s migration to Earth Engine doubled revenues while helping customers fight climate change through regenerative agriculture.
By vastly increasing the scope and precision of its soil carbon level maps, Perennial’s migration to Earth Engine doubled revenues while helping customers fight climate change through regenerative agriculture.
Enabling climate-smart agriculture at a global scale
One day David Schurman was looking for life on Mars when he thought of a way to combat climate change here on Earth. Shortly thereafter he co-founded Perennial, whose AI-enabled, Google Cloud–based datasets on soil health enable climate-smart agriculture at a global scale.
A native of Denver, Colorado, Schurman grew up in the shadow of the National Oceanic and Atmospheric Administration (NOAA) and the National Center for Atmospheric Research (NCAR) located in nearby Boulder, Colorado, and spent his high school summers interning at these world-famous scientific research institutes.
“I was working in an atmosphere lab at NOAA, analyzing air samples,” he recalls, “when we crossed the threshold of 400 parts per million of carbon dioxide in the atmosphere”—a key indicator of the seriousness of global warming. The experience was both seminal and visceral. “I knew then that I wanted to help find a way to heal the planet,” Schurman says.
But his own college and independent research in geoengineering left him discouraged. “Humans generate 40 to 50 gigatons of carbon emissions annually,” he laments. “There are few things that could even theoretically make a dent in that. I couldn’t find a climate solution that was both fast and scalable that didn’t come with bad unintended consequences.”
Perennial monitors, reports, and verifies soil data and agricultural greenhouse gases, and Google Earth Engine’s scalability, flexibility, reliability, and cost-effectiveness are enabling us to do so anywhere on Earth.
David Schurman
Co-Founder & Chief Product Officer, Perennial
Turning dirt into soil to save the planet
Disheartened, Schurman took a job at NASA’s Jet Propulsion Laboratories, where a spectral analysis of Martian rocks and soil was underway to determine if life had existed on the Red Planet billions of years ago. That project led to the idea for Perennial—co-founded with longtime colleagues and friends Jack Roswell and Oleksiy Zhuk—which fosters regenerative agriculture by monitoring, reporting, and verifying the amount of carbon in the soil on this planet.
“Soil hits the climate triage trifecta—it’s immensely scalable, readily available, and has very few unpredictable consequences,” he explains. “But 100 years of industrialized agriculture has released tens of billions of metric tons of soil-stored carbon into the atmosphere, leaving an over-warmed climate and a growing amount of unfarmable dirt. At Perennial, we’re helping turn that dirt back into soil.”
Performing this dirt-into-soil alchemy—the climate intervention tactic that underlies regenerative agriculture—involves incentivizing farmers and ranchers to change their practices in order to benefit the climate.
“Regenerative agriculture is not only changing how the food system works but how we manage the soil in which food grows,” Schurman continues. “But to do so, food companies and other agribusinesses have to be able to find the most promising arable land, and then measure and verify the amount of carbon that has reentered the soil.”
Monitor, report, and verify with Google Earth Engine
That’s where Perennial—and Google—come in. “Perennial monitors, reports, and verifies soil data and agricultural greenhouse gases, and Google Earth Engine’s scalability, flexibility, reliability, and cost-effectiveness are enabling us to do so anywhere on Earth," says Schurman, Perennial’s co-founder and chief product officer.
Google Earth Engine was the only platform that met our criteria for long-term scalability and also fit seamlessly into our existing workflows, which enabled us to get up and running quickly
David Schurman
Co-Founder & Chief Product Officer, Perennial
The process is about more than simply taking measurements—although together with their partners, Perennial collects tens of thousands of these. At Perennial, soil samples are combined with hundreds of data points from dozens of other sources, using proprietary algorithms to come up with “biophysical remote sensing data”—extremely accurate descriptions of the soil. Perennial uses compute-intensive AI- and ML-based modeling to generate these analyses and offers derived data products that predict future soil conditions.
The ultimate goal? “A foundation model for soils anywhere on the globe that will unlock soil as the world’s largest carbon sink,” Schurman states.
To reach that goal, Perennial decided to migrate its remote sensing data, orchestration pipelines, and data derived using AI modeling to Google Cloud. Flyte, Perennial’s open-source orchestration pipeline, which resides in Google Cloud as well, also makes use of the Kubernetes Engine and Google Cloud Compute Engine.
Meanwhile, the data points on lab-analyzed soil samples, which are used as the training data for Perennial’s AI modeling, were migrated to BigQuery.
Migrating terabytes of data, code, and pipelines in under three months
“After looking into all the available platforms, Google Earth Engine was the only one that met our criteria for long-term scalability and also fit seamlessly into our existing workflows,” Schurman notes, “and that enabled us to get up and running quickly, without having to reinvent the wheel.” He adds that Earth Engine’s 10-year history and large user community of researchers and companies with similar missions made him confident in the decision.
“I’ve worked with all three major cloud platforms, and Google Cloud is the only one whose individual components feel organically integrated,” he says. “That harmony among the features makes them easier to use, and their reliability keeps our engineers focused on product development rather than troubleshooting.”
Perennial teamed up with Google partner Woolpert Digital Innovations, which assisted in building a proof of concept for migrating terabytes of data: “We moved hundreds of thousands of rows of training data and all our orchestration pipelines to Google Cloud, as well as tens of thousands of lines of code and hundreds of thousands of data points spanning all our geospatial data products to BigQuery, in just under three months,” Schurman reports proudly.
Google Earth Engine allows us to work with any geospatial data set in novel ways and develop advanced AI models and datasets while keeping our engineering overhead low.
David Schurman
Co-Founder & Chief Product Officer, Perennial
Woolpert supported Perennial by sharing best practices for Earth Engine and even developed new predictive features for Perennial models that use Earth Engine data.
“The scale and sophistication of Perennial’s models require the kind of geospatial intelligence powerhouse that only a combination of Google Earth Engine and BigQuery can provide,” remarks George Azzari, director of AI at Woolpert. “It was clear to us from the start that Google Cloud was the perfect fit for Perennial’s tech stack and mission.”
Woolpert also introduced them to the Google team members most knowledgeable about the migration issues Perennial faced. “The Earth Engine team was rooting for us to succeed,” recalls Schurman, “and they remain engaged and excited by the ways Perennial is stretching the functionality of the platform.”
AI models 10 times faster, geospatial footprint five times bigger
That post-migration functionality has significantly boosted Perennial’s capabilities—and its revenues. “Since migrating to Google Cloud and Earth Engine, our AI model iteration speed is 10 times faster, the volume of data per iteration is 10 times larger, and the geographic footprint our data covers is five times bigger,” Schurman reports. “Google Earth Engine allows us to work with any geospatial data set in novel ways and develop advanced AI models and datasets while keeping our engineering overhead low.”
That translates into rapidly evolving models for global (rather than regionally limited) data products that can serve more people more quickly. As a result, Perennial doubled its revenue between 2023 and 2024, and is poised to quintuple 2024’s revenue in 2025.
“And because those data products are involved in helping to remove hundreds of thousands of tons of atmospheric carbon around the world, Google Earth Engine is helping Perennial have a very real, very positive effect on climate change.”
Using AI to increase global climate resilience
Perennial’s roadmap is leveraging those advantages to amass more datasets, build more accurate models for more regions, and make it easier for its customers to access and work with that data so they can expand their regenerative agriculture programs while making them more successful. Perennial’s launch of its Soil Ecosystem Map—a publicly available, interactive map of global soil health and carbon data—was its most recent step toward this goal.
“Google is the founder of much of the cloud-based geospatial ecosystem and shares Perennial’s mission of using advanced technologies and artificial intelligence to increase sustainability and climate resilience globally,” Schurman concludes, “so it really made sense for Perennial to become part of the Earth Engine community and support other researchers helping humanity through advances in climate science and remediation.”
Perennial provides compliance-ready measurement, reporting, and verification (MRV) for any crop and any regenerative agriculture program anywhere in the world. Its standards, tools, datasets, and ML-enriched digital soil mapping technology nurture regenerative agriculture by overcoming traditional MRV barriers of cost and scale.
Industry: Agriculture, Technology
Location: United States
Products: Google Cloud, Google Earth Engine, BigQuery, Compute Engine, Kubernetes Engine
About Google Cloud partner — Woolpert Digital Innovations
Woolpert Digital Innovations delivers comprehensive Google Cloud services and AI and geospatial solutions to optimize IT operations and enhance location-based services.
