Your methodology
Keep your logic, priorities, terminology and recommendation approach close to the workflow instead of leaving them in documents, spreadsheets or individual experience.
Your way of advising stays at the centre.
Whatever you grow in
Built for your crop — not just one way of farming.
Soil, substrate, sap or water; conventional, organic or regenerative. SoilBeat reads the data your system actually generates and builds the plan around it.
Open field & arable
Soil chemistry, base saturation and crop demand into a costed, season-long fertilisation plan from your own product list.
Greenhouse & glasshouse
Plant sap every ~3 weeks is an in-season blood test — it flags a deficiency up to three weeks before chlorosis shows.
Substrate & soilless
Driven by sap, drain and feed-water analysis — the levers that matter when there's no field soil to balance.
Built around the agronomist
A decision engine with the human in the loop — not a black-box chatbot.
Point a general chatbot at a farm's files and it reads PDFs as loose text, guesses the maths, and answers differently each time. SoilBeat keeps the logic explicit and the agronomist in control.
A raw chatbot
- You re-explain fields, zones, crops and history every time
- Sees documents, not data linked across seasons
- Can still guess the dose maths and conversions
- Text only — nothing reaches the farm workflow
SoilBeat
- Soil, sap, tissue, sprays, observations and yields linked by field and date
- Transparent models you can open up and adjust, not a black box
- AI drafts the plan; you stay in control of every decision
- Every answer traces back to your own numbers
Scale your expertise
Turn the way you advise into reusable knowledge.
Once the core advisory workflow is working, SoilBeat can help you capture what makes your advice yours — your methodology, specialist logic, products, priorities and way of working — and make it reusable across more recommendations.
Your modules
Turn specialist methodology into reusable recommendation modules for recurring questions, calculations or areas of expertise.
Repeat specialist knowledge without rebuilding it.
Your brand
Deliver recommendations using your own language, structure and branding, so the grower experiences your advisory practice — not a generic AI output.
Your expertise. Your presentation. Your relationship.
Your commercial model
Where the model fits, proprietary agronomic knowledge can become a reusable knowledge asset that supports new services, differentiated advisory products or monetisation.
Turn know-how into something that can scale.
The goal is not to replace the agronomist. It is to make good agronomy easier to repeat, extend and build on.
See how expertise can be configured