AgroMind is an insect-scale robotic system that monitors, diagnoses and treats crop threats at their earliest stage — deep inside the canopy, before damage becomes visible.
High-value crops are managed with limited visibility and delayed response. Critical threats start at the microscopic level, inside dense canopies that are inaccessible to inspection — and by the time symptoms are visible above the leaves, the damage has already spread.

Doesn't scale across large or dense crop areas. Limited to symptoms that are already visible.

Miss early-stage problems that develop at the leaf and fruit-cluster level — where they actually begin.

Applied across the whole field due to a lack of precise detection — expensive and damaging to the crop.

The grower still has to interpret the data and respond manually. The loop never closes.
AgroMind operates directly inside the crop canopy — sensing, diagnosing, treating, and verifying at the leaf level. From reactive, broad management to continuous, precise, autonomous control.
Identifies diseases, pest activity and plant stress before visible symptoms appear — while intervention is still cheap and preventable.
Delivers precise micro-doses directly to affected leaves or clusters. No blanket spraying, no chemical waste, no collateral damage to the crop.
Continuous 24/7 scanning, diagnosis and intervention. No manual scouting. Every plant monitored individually.
Coffee combines dense canopies, microscopic threats, labour-constrained operations and high crop sensitivity. Three of its most damaging problems are exactly the kind of failures AgroMind is built to solve.
Stopped at the microscopic stage. The system detects early infection before visible symptoms, treats the infected leaf directly, and confirms suppression through repeat scans — containing outbreaks before they spread.
Early invasion is detected at the fruit-cluster level, targeted micro-treatment is applied at the infestation site, and risk zones are continuously tracked and updated — reducing damage and broad-spectrum sprays.
Localised nutrient deficiencies are identified at the leaf level, corrected with precise micro-doses, and fed back into the field model — improving quality uniformity and yield consistency.
Critical threats begin at the microscopic level — exactly where existing tools can't see. Coffee's land and labour constraints make autonomous operation immediately valuable, and small biological improvements translate into outsized economic gains. The same platform extends seamlessly to vineyards, citrus, avocado and other high-value crops with similar canopy structures.
Modelled estimates based on target crops and current grower economics. Pilot validation to follow.
System architecture locked. First prototype unit. Core team formation across robotics, AI and agronomy.
1–3 robots operating inside the canopy. Basic vision AI on single pest. Closed-loop detect-treat-verify in controlled plots.
Commercial pilots across selected coffee orchards. Full digital twin. Grower-facing app.
Robot-as-a-Service rollout. Expansion to vineyards and adjacent high-value crops. International deployment.
We're looking for partners on the journey: engineers and researchers to advance the platform, growers and agronomists to pilot the system in real orchards, and strategic investors to scale the company.