Field intelligence from satellite, weather and farm data.
Keep farm records, monitor field conditions and connect observations with satellite, weather and soil context. Built for farmers and agricultural advisers who need practical decisions, not AI hype.
- Farm and field records
- Satellite field analysis
- Weather and soil context
- Diary, actions and reports
Start from a country, then move to the field.
ZaminAI can work in global mode, or adapt the entry experience to a selected country and preferred language. Country can suggest language, but it does not force it.
What ZaminAI helps answer
The homepage now leads with the actual agricultural workflow instead of abstract AI claims.
Where is the issue?
Use a saved boundary, detected plot, crop map field or manually drawn polygon.
What is happening?
Review satellite, weather, soil and field-context signals for the selected geometry.
How much changed?
Compare vegetation, moisture, rainfall and historical trend indicators where data exists.
Why may it be happening?
Explain contributing factors such as low rainfall, heat, cloud limits or diary events.
What should I inspect?
Turn analysis into scouting priorities, field checks, advisor questions and reports.
What problems does ZaminAI help solve?
ZaminAI is positioned around field decisions, not technology for its own sake.
Fields are hard to inspect frequently
Remote satellite and weather monitoring helps users prioritize where physical scouting is needed.
Crop stress can appear gradually
Vegetation and moisture indicators can highlight potential changes before they are easy to interpret by eye.
Irrigation decisions need context
Rainfall, temperature and vegetation signals help frame possible water stress without replacing field checks.
Disease-conducive weather is difficult to track
Where supported, humidity, rainfall and temperature context can flag elevated environmental risk.
Satellite data is technical
ZaminAI translates indices and weather context into understandable field-level explanations.
Organizations cannot visit every farm
Officer and program views support multi-field monitoring, prioritization and reporting.
From field selection to decision support
The operational analysis remains the existing working workflow. This homepage simply makes the path clearer.
Find or draw your field
Start from Analyze Field, Crop Map, saved fields or a manually drawn boundary.
Retrieve available data
Satellite, weather, soil and field geometry are connected to the selected plot.
Analyze field conditions
Vegetation, water-related signals, weather risk and historical context are evaluated.
Add farm context
Farm Diary, sensor readings and drone/photo records can add management evidence where available.
Act or monitor
Use the output for scouting, irrigation checks, advisor review, reports and follow-up observations.
From data to decision
Available now versus expanding integrations
Trust requires clear source labels. Planned integrations are not presented as already operational.
Satellite and field analysis
Existing analysis workflow uses field geometry and satellite indicators such as NDVI, EVI, SAVI, NDMI and related layers where supported.
Weather context
Weather routes and forecast/recent rainfall context are present in the operational application.
Soil and public geospatial data
Soil and environmental context are available as modeled/public estimates, not laboratory soil tests.
Farm Diary
Field observations, activities and records exist in the Grower Hub and can support future interpretation.
Sensors and drone records
The repository includes sensor-reading and drone-photo routes. The homepage labels this as connected data where configured, not universal live IoT.
Machinery and external farm systems
Future integrations may include machinery telemetry, irrigation systems and farm-management platforms.
Potential water stress signal
This is an example explanation, not a live diagnosis. It shows how ZaminAI should communicate uncertainty.
Field requires inspection
- ObservedVegetation trend declining
- Weather contextRecent rainfall low, high temperature
- InterpretationConditions suggest possible water stress
- UncertaintySatellite signal does not identify the exact cause
One complete crop workflow before expanding modules
The first usable ZaminAI product is farmer and adviser recordkeeping connected to available field intelligence.
Farm records
Register, create a farm, add fields, select a crop and keep a private season history.
Start recordsAnalyze Field
Open the existing map workflow to draw or select a plot and run available satellite/weather analysis.
Analyze fieldCrop Map
View and add field/crop locations, then pass the selected field into the same analysis flow.
Open mapDiary, actions and report
Record irrigation, fertilizer, treatments, observations, costs and harvest, then export history/report views.
Open Grower HubAsk ZaminAI
Ask field questions with available context. Answers must distinguish records, retrieved data and inferred advice.
Open Ask AIPayments
Subscriptions and online payments are not active yet. Start with a scoped paid pilot request.
Request pilotUseful extensions, clearly separated by readiness
These modules belong to the ZaminAI product direction, but they are not repeated across the page or presented as more complete than they are.
Officer Dashboard
Regional and institutional monitoring for fields, satellite layers, farmer plots and field prioritization where authorized data exists.
Open Officer DashboardZaminAI Academy
Training for farmers, advisers and officers on farm records, field analysis, satellite interpretation and responsible decision support.
Open AcademyValue Chain
Future connection layer for supply, market, processor and organization workflows. It should support the farm product, not replace it.
View future moduleDesigned for field users and institutions
ZaminAI should be useful from one field to regional agricultural programs.
Farmers
Monitor and understand their own fields with clearer field-level guidance.
Advisors
Support scouting, recommendations and field follow-up using environmental context.
Agribusinesses
Monitor multiple farms or production areas with consistent field records.
NGOs and development programs
Support remote agricultural monitoring and digital advisory work.
Government and extension
Prioritize fields, regions and crop-risk monitoring for field programs.
Researchers
Explore relationships between satellite, weather, soil and agricultural conditions.
A global architecture with local context
ZaminAI can potentially support agricultural monitoring where suitable satellite, weather and field data are available. Performance and interpretation may vary by crop, region and data quality.
Request a paid pilot
ZaminAI is ready to scope practical pilots for farmers, advisers and organizations. Pricing, payment provider setup and customer terms must be agreed before paid access or subscriptions are activated.
- Set up farm and field records for one crop workflow.
- Connect available satellite, weather and soil context to selected fields.
- Train users to record activities, observations, costs and harvest information.
- Produce a field history/report and define next configuration requirements.
Create a farm, add a field, record what happened.
The first workflow is practical: farm records, field context, observations, actions and reports. Field analysis remains available when satellite/weather configuration supports it.