In 2022, Iberdrola was looking for a solution to make its power lines more resilient.
The electricity company, which operates transmission and distribution lines across the U.S., Brazil, and Europe, had noticed that more trees were falling, likely because of an increase in extreme weather events. Falling trees and branches are often the main cause of failures in distribution networks, and Iberdrola needed a better tool to anticipate and minimize the risk.
To find it, Iberdrola launched a challenge through PERSEO, its start-up program. A few months later, it had a winner: Spanish start-up Woza Labs.
Woza Labs has multiple platforms that use artificial intelligence to improve data analysis, visualization, and risk forecasting. CEO Sebastian Priolo co-founded Woza alongside chief data officer Fernando Tadakuma in late 2020, after working for S4 AgTech, a company that uses satellite data to create parametric insurance for agriculture.
“The challenge was really clear,” he told Latitude Media. “[Iberdrola] needed more tools to improve their intelligence and the relation between their power lines and climate, weather and vegetation.” Woza’s product met Iberdrola’s needs.
Woza collects vast amounts of environmental, climate, and infrastructure public data — such as satellite imagery, photographs taken from planes and helicopters by private citizens, data from heat and weather sensors installed in cities and government buildings, and weather forecasts — and converts it into the same language. (“We obtain information every day from more than 7,000 sources,” Priolo said.)
Once that’s done, Woza combines the data with AI models to create modular predictive “layers,” or indexes that can be tailored to specific geographies and use cases, such as a model that uses water, soil, and weather data to predict vegetation growth, flooding risk, or wildfire probability. The layers are designed to be integrated into decision-making systems, digital twins, or monitoring platforms, and can make predictions out to 30 years.
The company then integrates private data from customers like Iberdrola — information about where their power lines are located, and historical data about failures in distribution networks — adapting a flexible digital twin, and creates a software that Iberdrola can use to make its own predictions, selecting the layers that best apply to its situation.
“When you input the information from an energy company’s facilities [in the platform], you understand the past incidents they suffered and the variables that explain those incidents,” Priolo said. The information is used to make both short-term and long-term risk assessments for new and existing power lines, which are then used by Iberdrola to make decisions about infrastructure upgrades.
Expanding verticals
Energy companies like Iberdrola are particularly exposed to worsening extreme weather events, and they’re very open to the benefits of predictive intelligence platforms like Woza. Seeing the obvious needs of utilities, Priolo is fundraising for an energy-only Woza “spin-off,” with a dedicated team that will work on developing energy-specific layers.
“But we’re applying our core model and idea to different verticals, like the agri-food business and government services,” Priolo said.
In the years since Priolo co-founded Woza, interest in adaptation technologies has been growing, as companies and governments face the immediate consequences of climate change on their infrastructure and supply chains.
For example, in its early days, Woza’s team developed a flood prediction layer that was mostly intended for soybean and corn crops. “For two years, when we showcased that layer at events, people were not interested,” said Priolo. “But recently, we’ve been seeing floods in many urban places, and governments are starting to think they can use it.”
Woza is also seeing attention from sectors that the startup didn’t expect.
“We closed a contract with a real estate client last week, and that was a surprise, because we didn’t think that real estate companies would need these complex variables to make decisions,” Priolo said. “But if we use our model to plan power lines, why can’t we use it for planning buildings?”
“We are always trying to create new layers for new verticals,” said Priolo.
The company is also exploring a predictive layer for carbon credits.. The tool would allow companies across energy, logistics, and infrastructure, to simulate project-level emissions based on spatial and design inputs.
“Right now, these simulations are mostly done by consulting services. But I want you to be able to simulate different scenarios with a simple click,” Priolo said.
