For large producers, cooperatives, contract farms, and agricultural insurers. Computer vision from drones and cameras, weather forecasting, predictive models for yields and animal welfare. AGROSTRATEG as a direct funding pathway.
Agriculture was the first sector to be computerised at tractor level. Now comes the second wave — at decision level.
Wrong timing on spraying, fertilisation, harvests. The costs are visible. The losses from a bad decision are rarely identified as losses from a decision.
On a farm with tens of thousands of animals, the critical signals of welfare, disease and anomalies are within camera range. No one is watching — there simply is no one available.
Yield forecasts that drive contract prices and policies often come from models built decades ago. AI lets us move from voivodeship-level to field-level precision.
Projects from other sectors whose pipelines are directly adaptable to AgriTech — with production metrics.
The same system that serves trading decisions in energy translates directly to spraying timing, fertilisation, and harvest planning in agriculture. Forecasts at 0.25° resolution and hourly granularity allow us to operate at the level of a single farm — not a region.
Pipeline originally built for roadworks detection from vehicle cameras — but its architecture (ViT-huge, training on 3M real + synthetic images, tolerance for variable weather) is directly adaptable to crop monitoring from drones, plant disease detection, and livestock welfare analytics.
Pipeline originally built for football analytics (player, referee, ball, field detection) with 30s video processed in < 1.5s. The same architecture — after swapping the training dataset — supports pig, poultry, and cattle farm monitoring: behavioural anomaly detection, individual identification, counting.
For the agricultural sector, 2026 offers exceptionally good timing — AGROSTRATEG closes on 28 August, with a PLN 300M budget.
NCBR's strategic programme for agriculture. Thematic areas T2 (environment) and T3 (production systems) are particularly well-suited to AgriTech projects with an AI component.
For AgriTech in a consortium with a research unit (e.g. IBiE, SGGW, UR Kraków). AI as the innovative component of the project.
Under the Common Agricultural Policy, support for precision farming at farm level — subsidies for implementation.
Food, bioeconomy, natural resources. Research projects in international consortia, up to 100% of costs.
Producer, buyer, processor, retail. AI solutions operate across the whole chain — we choose the point where they deliver the most value.
Where your organisation sits in the value chain, what data you already collect, where the biggest decision gaps are.
AGROSTRATEG, FENG, CAP, Horizon — each programme has a different logic. We match the project to the programme, not the other way around.
R&D unit (IBiE, SGGW, UR Kraków, IUNG), integrator (AIGP), technology partner, producer-recipient. Typical structure for AGROSTRATEG.
In agriculture, production means a field, a farm, a line. Implementation includes testing under real-world conditions.
A strong AGROSTRATEG application takes 4–6 months to prepare. If this call is on your radar — we start the conversation now, not in July.
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