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Artificial intelligence and automation for agriculture, fishing and tourism in Agadir. Forecast the season, automate the paperwork, and run the Souss-Massa operation on numbers rather than on habit.
Agadir drives the economy of southern Morocco. It is the largest sardine port in the world, the export capital for citrus and argan oil, and a major beach destination. Each of those runs on decisions AI is unusually good at improving.
The Souss plain is among the most productive farmland in Africa, and it is running short of water. Precision agriculture (soil probes, satellite imagery, predictive models) makes every litre and every kilo of fertiliser count. At sea, shoal prediction and fleet routing cut fuel while keeping the catch inside quota.
We build for the Agadir context specifically: the farms, the canneries, the cold chain operators and the hotels.
Our models learn from Souss-Massa conditions: a semi-arid climate, a tourist season with a shape of its own, and fishing cycles no imported template accounts for.
We deploy in measurable stages: one profitable use case inside eight weeks, then more. Nothing you currently run gets replaced to make room.
Citrus, argan, fishing and coastal tourism. We can hold a conversation about your trade before we start one about ours.
Our AI solutions in Agadir
Yield forecasting from satellite imagery and soil probes, drip irrigation tuned to what the ground is actually doing, early disease detection, and input planning for citrus and early-vegetable growers.
Multilingual chatbots for hotels and riads, yield management that holds its nerve in high season, and recommendation systems for activities and excursions.
Fishing ground prediction from currents and sea surface temperature, route optimisation, live cold chain monitoring, and traceability from the boat to the cannery door.
European demand forecasting, packing house planning, refrigerated transport coordination and customs paperwork that fills itself in.
The same technology behaves very differently on a farm and on a trawler, so we calibrate it per sector.
FAQ
The range commonly seen on the Souss plain is fifteen to thirty percent, and it is wide because it depends entirely on where you start. A farm already running drip irrigation with soil probes will gain less than one still watering to a calendar. We measure your current consumption before putting a number on it.
Yes, because agricultural sensors do not use the ordinary mobile network but long-range low-power protocols that carry several kilometres. Readings are stored locally and sync as soon as a gateway is reachable. A network outage therefore delays the reporting, it does not lose the data.
That is exactly what the collected data produces, provided it is structured from the plot onward. We link inputs, harvest date, packing station and shipped container. A buyer asking for the history of a citrus pallet then gets a dated record, rather than a reconstruction assembled from memory three weeks later.
It is useful without being a certainty, and it should be described that way. Models combine surface temperature, satellite data and past campaigns to rank areas by probability, which cuts search time and therefore fuel. No model will tell you where a shoal is, but it will rule out the unlikely areas.
Irrigation gains show up on the water and energy bill within weeks, whereas yield models need at least one full season before they are credible. So we start with water management, which measures quickly, and come to prediction afterwards, since it needs your own history to be worth anything.
Ask for a free AI maturity check. We name the use cases worth the money in your business and send an action plan within 48 hours.