AI for Agriculture
From field trial analysis and residue management through to a production platform.
Supper & Supper builds AI solutions for crop science and digital farming.
Agricultural science is not an add-on qualification for us
We have worked for leading agribusinesses for years – from the analysis of field trials, to reducing the environmental impact of crop protection products, to the residue management platform that serves thousands of users at Bayer Crop Science.
Our data scientists hold PhDs – in agronomy, biology, chemistry, mathematics, physics and statistics. So the people talking to your scientific functions are people who do not need trial design, compound pipelines or residue analytics explained to them first.
And we deliver end to end: from the first proof of concept to a production platform serving thousands of users, which you will run for years. As an extension of your own team where that suits you better.
What does AI mean in agriculture?
AI in agriculture combines algorithms, machine learning and data analysis to automate agricultural processes and enable data-driven decisions. Data from satellite imagery, sensors, weather forecasts and soil analyses is processed and translated into actionable insight – for better planning, execution and monitoring in the field.
This addresses the sector's central challenges: growing demand for food, scarce resources and adaptation to climate change.
Reference projects
ResiYou platform for Bayer Crop Science. AI-driven residue management that brings together requirements from a large number of departments – from the first models to a production platform serving thousands of users.
Soon after the Supper & Supper team begun to work on the project we started to see the results: our predictive models increased the accuracy tremendously and the feed-back of our customers turned to be extremely positive.
– José Luis Robles Martín, New Venture Lead EMEA – Horticulture, Bayer
Reducing the environmental impact of crop protection products. Data-driven assessment and control of product application, aimed at lowering environmental impact while maintaining efficacy. View the use case →
Automated pipeline for field trial analysis. Evaluation of large trial series in a pipeline that is usable without a technical background and supports decisions directly – complemented by explainable models that make clear which factors drive a result. View the use case → · Explainable AI for field trials →
Where we apply it
- Residue management: forecasting and controlling residue levels along the application recommendation, as in Bayer Crop Science's ResiYou platform.
- Field trial analysis: automated analysis pipelines with explainable models, usable without a technical background.
- Decisions in the compound pipeline: predictive models for candidate prioritisation – many candidates, sequential gates, expensive field trials.
- Remote sensing and geodata: evaluation of satellite, aerial and drone imagery for the early detection of pest infestation, disease and environmental stress. → Geo AI
- Data foundation and operations: scalable structures for soil, weather and sensor data, MLOps, monitoring and retraining.
Digital farming and crop science
Digital farming uses sensors, drones, AI and satellite data to optimise production, conserve resources and enable data-driven decisions. In crop protection, AI detects pest infestation, disease and environmental stress early; in residue analytics it supports compliance with limit values.
- Models trained specifically on soil, weather and field research data
- Scalable platforms for sensor, satellite and drone data
- Detection of plant diseases and anomalies through pattern recognition
- Precise residue analysis for the highest quality standards
From proof of concept to platform
Most AI initiatives fail not at the model but at the transition into operation. We cover the entire chain ourselves – you do not need a second partner for industrialisation.
- Data Consulting – clarify the question and the data situation
- Data Lab – prototype on your data
- Data Operations – production use with MLOps
- Data Infrastructure – scalable cloud architecture, hosting in Germany and the EU
Working together: data security and regulatory context
We are certified to ISO/IEC 27001:2022 (TÜV Rheinland, reg. no. 01 153 2300149). Processing and hosting take place in Germany and the EU. We use client data solely for the agreed project and never to train our own models. We provide the certificate and our documentation of technical and organisational measures to your procurement team on request.
Where results feed into registration or residue questions, we supply the documentation your specialist function needs for its evidence trail. For the requirements of the EU AI Act we offer our AI Compliance Check.
Let's talk about your project
Whether it is field trial analysis, residue forecasting or a platform for your specialist teams: we start with an appraisal of your data situation, not with a proposal.