MEET THE TEAM

Jay McEntire
CEO, CoFounder
Experienced Fintech CEO, former bank holding company CFO and investment banker. Managing Director of Glennoe Farms, LLC. Successful exit as CEO of ProTrader Group to Instinet for $150M.

Jay McEntire
CEO, CoFounder
Experienced Fintech CEO, former bank holding company CFO and investment banker. Managing Director of Glennoe Farms, LLC. Successful exit as CEO of ProTrader Group to Instinet for $150M.

Ben Brown PhD
Chief Machine Learning Architect, CoFounder
Machine Learning Expert & Head of Molecular Ecosystems Dynamics at Lawrence Berkley National Laboratory, Chair of Environmental Bioinformatics at U of Birmingham, and Senior Scientific Advisor for Preminon, LLC.

Jay McEntire
CEO, CoFounder
Experienced Fintech CEO, former bank holding company CFO and investment banker. Managing Director of Glennoe Farms, LLC. Successful exit as CEO of ProTrader Group to Instinet for $150M.

Mark Isbell
Founding Board
Member, Rice Farmer
Rice Farmer with Isbell Farms and Instructor of Professional Tech Writing at University of Arkansas Little Rock. Board Member of Sustainability Committee USA Rice Federation. Board Member of Field to Market.

Jay McEntire
CEO, CoFounder
Experienced Fintech CEO, former bank holding company CFO and investment banker. Managing Director of Glennoe Farms, LLC. Successful exit as CEO of ProTrader Group to Instinet for $150M.

Matt Rholik
Managing Director of Farm Data, Strategic Partnerships
Experienced farmer and rancher, 15 years precision agriculture expert specializing in equipment (John Deere for 10 years and remote sensing with Mavrx and Taranis Inc)
MEET THE TEAM

Nathan Slaton
Advisor
Assistant Director now Agriculture Experiment Station for the University of Arkansas, leading two labs specializing in agricultural analyses, testing services, and fertilizer recommendations.

Merle Anders
Advisor
Consultant for Unilever, sustainability, and Ducks Unlimited, water resources, Former Rice Systems Agronomist for the University of Arkansas Rice Research and Extension Center, and international soil scientist.
OUR STORY
At Arva Intelligence, we are farmers first. Our challenges are the same as yours, especially when dealing with data. We had collected data for years, but had little success turning that data into something actionable — USB drives, file folders, and binders were piling up, and our devices were full of farm apps. We decided to do something about it and took the challenge head on.
After three years of an on-going research collaboration with Lawrence Berkeley National Lab, Oak Ridge National Lab, and the University of Arkansas, we founded Arva Intelligence in 2018. Now, we're bringing farmers, suppliers, and manufacturers the same technology we use to streamline decision making for agronomics, economics, and sustainability.
As a deep technology B-Corporation, Arva Intelligence is deeply committed to protect the economic profitability of farmers and the environmental health of farmland. We continue to create, innovate, and deploy cutting-edge machine learning and artificial intelligence technology to enhance our ability to scale profitable and sustainable agriculture.
Rooted in Research
Arva Intelligence’s roots in greenhouse gas emission modeling and carbon sequestration studies began in 2016 with the AR1K research collaborative. Glennoe Farms, the University of Arkansas, along with Lawrence Berkeley and Oak Ridge National Laboratories, took the latest in environmental science and remote sensing technology from the lab to the field, compiling dense data and real-world application on over 1000 acres in Arkansas. The results of AR1K led to the artificial intelligence models that became Arva Intelligence. Today, Arva is still deeply involved in research and development, collaborative projects, and environmental research.
Contributions to Climate Science

GHG to Carbon Sink in Precision Ag
From GHG Emissions to Carbon Sink with Precision Ag: Arva is leading an ARPA-E SMARTFARM research in data science from agricultural GHG footprints to validate and enable regenerative land management practices that capture ecosystem service values for farmers.

Carbon & N2O Quantification
As part of a Phase II ARPA-E team, Arva is collaborating with Dagan and Veris Technologies to build a scientifically sound, scalable N2O quantification platform that will solve the challenge of quantifying hot spots and hot moments of N2O fluxes by integrating advanced sensing technologies with the DNDC biogeochemical model for understanding the drivers of N2O fluxes.

XAI Models for Terrestrial Carbon Cycles
In concert with Lawrence Berkeley Labs and the University of Arkansas, we are developing deep learning XAI models to extend our predictive understanding to the terrestrial carbon cycle for three commodity crops, aiding farmers to profitably mine the atmosphere for carbon, improving soil health and to reduce the need for non-renewable inputs.