abfAgri connects live satellite imagery, open-source AI agents, and consequence modelling to tell fertilizer producers across the SADC region exactly where crop stress is happening, what it will cost if untreated, and which of your products fixes it — field by field, in under 5 seconds.
✅ Omnia product recommendation
Trusted by SADC's leading fertilizer & agri-input producers
Most agri-AI stops at prediction. abfAgri models how effects propagate through the crop system, quantifies what inaction costs in ZAR, and serves the optimal product recommendation from your catalogue — closing the loop from satellite pixel to sale.
| Alert-based AI (e.g. mAgri) | abfAgri — Consequence Model |
|---|---|
| "Nitrogen deficiency detected" | "N deficiency → 23% yield loss in 7d → R 41,200/ha at risk" |
| Diagnoses from a single photo | Correlates photo + live NDVI + soil moisture + weather forecast |
| "Apply fertilizer" (generic) | "Apply Omnia LAN 28% @ 150kg/ha within 48h → 92% recovery" |
| No revenue attribution loop | Tracks recommendation → purchase → yield outcome → reorder |
| Consumer app — no B2B data | Producer dashboard with territory & geospatial heatmaps |
| Pan-African — no SADC specificity | Calibrated per SADC country: soils, crops, seasons, regulations |
Sentinel-2/Landsat NDVI, soil moisture anomaly, and weather overlays fused with farmer's field photo. Precise farm-boundary data pulled from live satellite feeds.
Causal graph propagates: NDVI decline → nutrient stress → growth inhibition → yield reduction → ZAR revenue at risk — quantified for actual field size and current commodity price.
Best-fit product selected from your catalogue. Application rate, method, and intervention window specified. Farmer sees net ZAR gain vs cost of inaction — no convincing needed.
Purchase data feeds back. Outcome data improves the model. You see which products moved where, and why — compounding accuracy and commercial advantage over time.
abfAgri's engine layers geospatial state, temporal evolution, causal reasoning, multi-scenario simulation, and profit-optimised recommendation — moving producers from reactive alerts to anticipatory, consequence-aware commercial intelligence.
Fuses satellite vegetation indices, soil moisture, weather, GPS field boundaries, crop stage, and field observations into a single geospatial field intelligence layer. Handles connectivity gaps common across SADC rural areas automatically.
Tracks NDVI trajectories, soil moisture trends, and crop growth stage curves across the season. Detects stress before visible field symptoms, maps seasonal demand patterns, and forecasts product requirement windows by geography.
Maps causal pathways: low N → reduced chlorophyll → NDVI decline → stunted growth → yield loss → ZAR revenue risk. Enables intervention reasoning that distinguishes correlation from cause — so recommendations are defensible, not probabilistic guesses.
Simulates Product A vs B, apply now vs in 3 days, 100 vs 150 kg/ha — presenting each as a concrete ZAR ROI scenario. Turns field uncertainty into structured, comparable choices. Agronomists and farmers see tradeoffs explicitly, not intuitively.
Evaluates simulated interventions against farmer objectives (yield recovery, cost) and your commercial constraints (product availability, margin, geography). Outputs a ranked recommendation — your SKU, rate, timing, delivery — with full justification the farmer trusts and your sales team can track.
Satellite-derived field intelligence across all 16 SADC member states — stress detection, revenue opportunity sizing, and Omnia product recommendations. Click any country or pulsing opportunity zone for full intelligence.
← Click any country or zone on the map
abfAgri runs a four-stage intelligence pipeline that converts field satellite data into a diagnosis, a financial consequence, and a ranked product recommendation — in under 5 seconds. Each stage is purpose-built for SADC agri-commercial decision making.
Continuously monitors every field across 16 SADC countries using live satellite imagery. Detects vegetation stress, soil moisture shifts, and weather risks — automatically, before a farmer or agronomist even visits the field.
Identifies what is wrong with the crop — nutrient deficiency, pest pressure, disease, or water stress — with a confidence rating and severity level. Covers 40+ SADC crop varieties and gives a plain-language explanation of the root cause.
Converts the diagnosis into a financial outcome: how many tons of yield are at risk, what it is worth in rands, how many days until the loss becomes unrecoverable, and what recovery is possible if action is taken today.
Selects the top 3 products from your catalogue ranked by yield recovery and commercial return. Gives the farmer the exact product name, application rate, timing, and projected rand gain per hectare — ready for the agronomist to act on.
Select your crop, describe what you're seeing, and abfAgri's AI identifies the problem, quantifies yield risk in rands, and recommends the exact Omnia product — with ROI per hectare.
← Select your crop type to begin the analysis
Evidence-based intelligence connecting live SAFEX prices, satellite field data, and SADC crop science into insights for Omnia's field teams.
Upload a crop or field photo — abfAgri's vision AI analyses it in seconds and delivers an agronomic diagnosis with targeted Omnia product recommendations.
Omnia's R8.9B agriculture segment serves the exact farmer base abfAgri's consequence engine addresses. abfAgri adds the AI intelligence layer that converts every agronomist visit, every co-op conversation, and every field observation into a consequence-quantified Omnia product recommendation — in rands, in real time, at scale across all 8 SADC operating countries.
Real data from public annual reports, JSE filings, FASA Fertilizer Reviews, and FAO statistics. No fabricated market share figures — cited per source.
Omnia and Yara have broad SADC distribution but operate with traditional sales models — no consequence modelling, no field-level AI recommendations. Their scale is a distribution advantage, not a digital moat.
YaraConnect provides basic weather alerts and crop calendars. It does not model yield loss, quantify financial risk in ZAR, or generate SKU-specific ROI recommendations. The capability gap to abfAgri's 5-layer stack is substantial.
Omnia's R8.9B agriculture segment serves the exact farmer base abfAgri's consequence engine addresses. Licensing abfAgri into Omnia's co-op and retail network turns every agronomist visit into a ZAR-quantified consequence conversation — driving product pull-through at scale across 8 SADC countries.
Six high-conviction growth opportunities identified from satellite field data, SAFEX price signals, and SADC agronomic gap analysis. Each pocket is sized by addressable revenue and ranked by time-to-close.
Full closed loop — recommendation → purchase → yield outcome → reorder signal. See exactly which AI recommendations drove which sales across which territories.
Deploy under your brand in weeks. Your app, your colours, your farmer relationships — abfAgri's consequence engine running silently underneath.
REST + GraphQL API connects field diagnostic data into your ERP, CRM, or order management system. Geospatial stress signals flow directly into your commercial workflows.
Consequence reports delivered in isiZulu, Afrikaans, Shona, Chichewa, Kiswahili, Portuguese, French, Malagasy, and more — ensuring adoption across all farmer segments.
POPIA (SA), PDPA (Tanzania), and SADC data localisation compliant. Farmer data stored in-country. Zero third-party harvesting. You own your farmer relationships.
Executive dashboards showing territory-level crop stress, product demand forecast, revenue attribution, and seasonal opportunity maps — ready for quarterly business reviews.
abfAgri changed the conversation with our co-op partners entirely. The consequence model shows farmers their yield risk in rands — not agronomic jargon. Our Fertasa product attachment rate at the counter jumped 38% in the first season.
The satellite heatmaps are exactly what our Highveld sales team needed. We now pre-position LAN and potassium before demand peaks — not after. The geospatial intelligence gives us a genuine week's head start over competitors.
We white-labelled abfAgri as "NutriFlo Advisor" in eight weeks. The open-source agent stack means we're not locked into any cloud AI vendor. Limpopo citrus farmers use it daily — micronutrient retail sell-through is up 35%.
Select a field scenario or enter your own parameters. The AI pipeline returns a diagnosis, yield impact, and product recommendation in seconds.
Real-time news from Grain SA, Farmer's Weekly, and SADC sources — filtered for what matters to Omnia's commercial strategy.
You have the distribution scale, the brand trust, and 8 SADC markets. abfAgri has the consequence AI, the satellite intelligence layer, and the commercial engine that turns every agronomist visit into a verified sale. Together, this is a R 2.3B closed-loop opportunity — no competitor has it.
90-day pilot · Revenue-share or license model · POPIA compliant · Deploys in under 2 weeks
