Victoria Tostado Bringas, founder of Agxes, identified a problem that no one had solved: agricultural producers could not access credit because banks did not understand their technical information. Thus was born a platform that translates agronomic data into financial language using AI.
From Veracruz to MIT: how the idea was born
Victoria Tostado Bringas grew up in Coatzacoalcos, Veracruz, a city marked by the oil industry and its constant economic crises. That led her to explore alternatives for her region, and she found agriculture a vocation with enormous potential.
He formed his own agricultural production company, with tomato greenhouses and Persian lime trees for export. He then worked alongside state governments and a development bank, where he understood the problem from both sides: that of the producer and that of the financier.
With that clarity, he decided to go to MIT to find the technological tools to solve what he saw every day: an information gap between those who produce and those who lend.
“I understood that both parties wanted to get to know each other, that both parties wanted to collaborate, but a layer of intelligence was needed to transform the technical agronomic information into a financial language of credit quality,” declared Victoria Tostado Bringas, founder of Agxes.
Start as a woman in a sector that did not expect you
Victoria Tostado Bringas acknowledges that, if she had known all the obstacles she would face for the simple fact of being a woman, perhaps she would not have started. And just in that he finds a lesson: conviction makes you start, and once inside, there is no turning back.
The biases were not always evident. In her first company, linked to the industrial sector, an engineer who welcomed her assumed from the outset that she worked with her father. The company, of course, had been founded by her.
Far from becoming bitter, Victoria adopted a philosophy that accompanies her to this day: always enter with the best attitude, correct as you go and demand recognition with respect.
“The only limitation we could have is the one we create for ourselves,” said Victoria Tostado.
How Agxes works
The platform combines three AI technologies. First, Vision Language Models to extract and organize information from documents automatically. Second, Large Language Models to interpret quantitative data, such as satellite vegetative indices or financial ratios, according to the rules of each banking institution. Third, machine learning models for financial and market price predictions.
The result: analyzes that once took weeks are now completed in five to ten minutes. And implementations, which in traditional technology could take up to a year, today are closed in two to three weeks.
What’s coming for Agxes
The company has its sights set on becoming the global standard for agricultural credit. Their vision goes beyond financing: they want to enable the transition towards organic agriculture, irrigation systems and crops more resilient to climate change.
“Agxes is going to be the standard in how agricultural credits are generated, managed and placed,” declared Victoria Tostado Bringas.
By 2026, the focus is on consolidating its first clients in the US non-bank financial sector, expanding academic collaborations and moving towards larger scale agricultural banks.
