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Digital Ag Global, Season 2, episode 9, Smart Algorithms in Agriculture
Season 2
Episode 9
Published 7 hours ago
Description
Digital Ag Global: Smart Algorithms in AgTech — Building Forecasting & Intelligence Solutions
Artificial intelligence in agriculture is evolving far beyond dashboards and marketing buzzwords.
In this episode of Digital Ag Global, we explore what it really takes to build forecasting and intelligence systems that can support real agricultural decisions — from yield forecasting and nitrogen efficiency to carbon quantification, climate reporting, and agronomic optimization.
Joining us is Tatiana Boussange, General Director & Co-founder of Armosys, a spin-off from the University of Milan behind ARMOSA — a process-based modelling engine designed to power carbon, climate, and productivity intelligence across agricultural supply chains.
Together, we’ll discuss:
• What “smart algorithms” in agriculture actually mean today
• The difference between scientific engines and simple analytics dashboards
• Which agricultural problems are truly ready for algorithmic decision-making
• Why data quality matters more than model complexity
• The role of soil, weather, satellite, and management data in forecasting systems
• How companies build defensible, audit-ready intelligence solutions for carbon and Scope 3 reporting
• Why regional calibration is critical for credible outputs
• The future of AI, process-based models, and algorithmic decision-making in agriculture
We’ll also examine one of the biggest shifts happening in AgTech right now: the move from isolated sustainability reporting toward integrated decision engines that combine productivity, carbon, climate, and operational intelligence into a single system.
This conversation is especially relevant for:
→ AgTech founders
→ Food & agrifood companies
→ Carbon and MRV platforms
→ Sustainability leaders
→ Agronomists and technical advisors
→ Precision agriculture innovators
→ Data and AI teams building agricultural solutions
Hosted by Yurii Kovalchuk and Clyde Graham on Digital Ag Global.
Artificial intelligence in agriculture is evolving far beyond dashboards and marketing buzzwords.
In this episode of Digital Ag Global, we explore what it really takes to build forecasting and intelligence systems that can support real agricultural decisions — from yield forecasting and nitrogen efficiency to carbon quantification, climate reporting, and agronomic optimization.
Joining us is Tatiana Boussange, General Director & Co-founder of Armosys, a spin-off from the University of Milan behind ARMOSA — a process-based modelling engine designed to power carbon, climate, and productivity intelligence across agricultural supply chains.
Together, we’ll discuss:
• What “smart algorithms” in agriculture actually mean today
• The difference between scientific engines and simple analytics dashboards
• Which agricultural problems are truly ready for algorithmic decision-making
• Why data quality matters more than model complexity
• The role of soil, weather, satellite, and management data in forecasting systems
• How companies build defensible, audit-ready intelligence solutions for carbon and Scope 3 reporting
• Why regional calibration is critical for credible outputs
• The future of AI, process-based models, and algorithmic decision-making in agriculture
We’ll also examine one of the biggest shifts happening in AgTech right now: the move from isolated sustainability reporting toward integrated decision engines that combine productivity, carbon, climate, and operational intelligence into a single system.
This conversation is especially relevant for:
→ AgTech founders
→ Food & agrifood companies
→ Carbon and MRV platforms
→ Sustainability leaders
→ Agronomists and technical advisors
→ Precision agriculture innovators
→ Data and AI teams building agricultural solutions
Hosted by Yurii Kovalchuk and Clyde Graham on Digital Ag Global.