AI for the Horticulture Sector
Labour is scarce, costs are rising and cultivation decisions are becoming increasingly complex. With you get more value from your data and control your cultivation process in a smarter, more predictable and more efficient way.
The challenges in the horticulture sector
- Labour shortages
- Versnipperde kennis over wet- en regelgeving
- Tijdsintensieve administratie en rapportage
- Inconsistente besluitvorming tussen teams
- Toenemende complexiteit van casuïstiek


How AI solves these challenges
Onze AI-oplossingen zijn ontworpen om professionals te ondersteunen, niet te vervangen. Dat doen we via drie strategische pijlers:
Predictive demand ML models
We accurately predict demand and sales based on historical data, seasonality and market developments. This way, you can plan production and logistics smarter and prevent surpluses or shortages.
AI contracts management
AI analyses and manages contracts automatically, identifies risks, monitors maturities and obligations and provides immediate insight into contract information. This saves time, reduces errors and increases compliance.
AI staff planning
AI aligns staff deployment to current and expected needs. By taking into account availability, skills and workload, efficient planning with lower costs and higher productivity is created.
The seniority level that matches your project
Step 1 — Analysis & Goal-Setting
We map processes, data, systems and bottlenecks. Together, we determine where AI adds the most value and formulate clear, measurable goals.
Step 2 — Data inventory & feasibility
We analyse available data for quality, completeness and usability. In addition, we test the technical and organizational feasibility of the AI solution.
Step 3 — AI concept & solution design
Based on the insights, we design a concrete AI concept, including models, architecture and integrations with existing systems.
Step 4 — Development & Validation
We develop the AI models and software and validate them with realistic scenarios and real-world data to ensure reliability and accuracy.
Step 5 — Implementation & Integration
The AI solution will be integrated into your existing IT and cultivation systems, with minimal disruption to daily operations.
Step 6 — Training & Adoption
We ensure that users understand and trust the AI. Through training and guidance, the solution is effectively deployed in practice.
Step 7 — Monitoring & further development
After going live, we monitor performance, adjust where necessary and continuously develop the solution based on new data and insights.











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