Answers to keep your project moving

Crop Urbanis is a science-led agritech company led by Ilia Sukhodolov, a plant scientist and international consultant specialising in vertical farms, greenhouses and resilient food systems. The business combines consulting, training, research and an expert-reviewed AI/data decision-support product for controlled-environment agriculture.

Clients include agritech startups, investors, equipment suppliers, retailers, hospitality groups, universities, NGOs, municipalities and existing farm operators looking to launch or optimise controlled-environment facilities. Early engagement reduces risk and saves cost.

No. We design and optimise production in vertical farms, greenhouses, hybrid or retrofitted spaces and compact urban sites—from restaurants and hotels to research labs, rooftops and logistics hubs. If a space can host utilities and basic climate control, we can adapt a system.

We cover feasibility, crop and system selection, layout and technology recommendations, nutrient and IPM programmes, SOP creation, team training, remote/onsite supervision, business modelling and CAPEX/OPEX planning tailored to your goals.

Yes. Engineering & Tech Specs engagements benchmark lighting, climate, fertigation and automation stacks, provide integration roadmaps and coordinate with vendors during procurement.

Lettuce and leafy greens, tomatoes, cucumbers, peppers, eggplant, culinary herbs, saffron, mushrooms, edible flowers, fodder/microgreens and more. We tune systems for the crops you need.

Yes. We support clients remotely and on-site across Europe, the Middle East, Africa, North America and Asia with consulting, training and supervision. Travel plans are scoped during kickoff.

A: Yes. All curricula, signage and facilitator guides can be delivered in six languages — English, French, Russian, Spanish, Chinese, and Portuguese — with localisation workflows defined from the outset.

Strategy and feasibility sprints run 4–6 weeks, commissioning programmes 8–16 weeks, and optimisation retainers adapt to crop cycles. We confirm milestones, deliverables and governance checkpoints during scoping.

Crop Urbanis delivers science-led agronomic consulting, training and research support today, while also developing a pilot-ready AI/data decision-support product for selected partners. The technology product does not replace the service business; it productises repeated CEA workflows into structured digital tools.

It is a controlled-environment agriculture decision-support product that structures project data, crop protocols, feasibility assumptions, SOPs, KPI tracking and operational knowledge into expert-reviewed workflows for vertical farms and hydroponic greenhouses.

AI is used or planned for agronomic knowledge retrieval, multilingual SOP and training generation, crop and operations diagnostics, model evaluation, document processing, dashboard support and computer-vision or sensing experiments. AI outputs remain subject to expert agronomic review and are not used as autonomous final decisions.

Cloud infrastructure supports secure data storage, API hosting, dashboards, project workspaces, document processing, model inference, image/sensor workflows, monitoring, logging, backups and collaboration with research or pilot partners.

Relevant inputs include site layouts, utility capacity, crop targets, cultivar choices, yield history, nutrient and climate protocols, labour assumptions, CAPEX/OPEX models, regulatory constraints, SOPs, supplier documents, pest or disease observations, post-harvest data, images and sensor readings where available.

No. Crop Urbanis treats AI as a support layer for structured analysis, retrieval, drafting and monitoring. Final recommendations remain reviewed by an agronomy expert and adapted to crop biology, facility constraints, climate, labour, market and safety context.

Not as a public self-serve SaaS. The technology layer is pilot-ready with selected partners, where scope, data access, review process, infrastructure and deliverables are defined case by case.

Yes. Crop Urbanis is open to partnerships around greenhouse data structuring, AI-assisted agronomy, computer vision, sensing, model evaluation, multilingual training workflows, cloud dashboards and pilot validation in controlled-environment agriculture.

Project data is used for the agreed engagement or pilot scope. Sensitive farm, supplier, financial and operational information should be handled under appropriate contractual and confidentiality terms. Where third-party cloud or AI processors are used, data handling and access conditions should be defined before deployment.

AI tools in agriculture need agronomic ground truth. Crop Urbanis brings field experience across vertical farms, greenhouses, hydroponic systems, crop nutrition, climate-control experiments, commissioning, training, SOPs and international projects. That domain base helps define what software should measure, what outputs require review and where automation is actually useful.

Share site layouts, utility capacities, crop targets, historical yields, budget ranges and regulatory constraints. We use this data to tailor models, risk assessments and KPI tracking from day one.

Yes. Training, SOPs & Remote Support missions, plus the Hydroponic Nutrient Solutions masterclass and free microgreens course, deliver hands-on coaching, calculators and bilingual materials.

Live cohorts provide workbooks, nutrient calculators, lab templates and follow-up coaching notes. The microgreens programme ships printable checklists, sowing-density charts, troubleshooting flows and regional supplier shortlists so teams can act immediately.

We provide post-launch optimisation plans, analytics dashboards and governance playbooks so teams can monitor KPIs, manage crops and update SOPs. Retainer support is available when ongoing tuning is required.