IrrigAimsSense. Decide. Act. Learn.

Questions, answered.

Product, pilots, data and AI, and company: the same maturity labels used everywhere else on this site apply here too. Nothing below is presented as more finished than it is.

Product

What does an AgroSense pod actually sense, and do with it?

An 8-in-1 soil probe reads moisture, temperature, EC, pH, nitrogen, phosphorus, potassium and salinity from a single insertion point, alongside a Sensirion SEN54 air-quality sensor and an onboard camera, all sampled on the same cycle. The pod then closes the loop itself: on-hub models decide whether to water, the pump runs, and every litre delivered is metered per cycle.

Does a pod need WiFi or mains power?

No. Each pod runs on its own solar supply and talks to the hub over a LoRa radio link with km-class range by module spec: no mains wiring and no WiFi required in the field.

What's the difference between AgroSense, AgroSense+ and AgroSense Pro?

Three planned tiers: AgroSense covers base sensing and control, AgroSense+ adds the programme-year AI layer, and AgroSense Pro adds fleet and reporting features. Hardware pricing is published on Products, priced by the line and quoted per site; software is a planned subscription, quoted per site.

Pilots

How does a pilot actually start?

With a metered baseline. Before any hardware goes in, we record current water use so every later figure has something real to compare against. Then pods are installed, the system runs and logs every cycle, and results are published once measured.

When do you publish pilot results?

Once they're measured, never before. A published figure carries its measurement period, baseline, formula and source attached: see Climate Impact for the full methodology.

Is the hardware I'd be piloting production-ready?

Today it's a bench-validated prototype, running end-to-end. A production carrier board is scoped and costed specifically for the pilot batch: see Technology for the full bill of materials.

Data & AI

How many models make the irrigation decision, and where do they run?

Six decision-forest models run directly on the LoRa hub in the field, not in the cloud, and retrain nightly against real field data through an automated pipeline: no laptop, no manual step.

Is the data shown on this site real?

Yes, where it says so. The dashboard at app/, the telemetry ribbon, and the pod, hub and salinity panels read the live field pod directly. Multi-site fleet views need more than one site to be legible, so the additional sites are illustrative and carry an Example fleet chip. Pod data never does.

Which AI features are shipping, and when?

Twelve features are defined for the current build. Eleven are built: WaterIQ, both Savings Ledgers (water and nutrients), AgroBrain, NutrientIQ, FertiBrain and SproutID, plus LeakSense, SensorGuard, SaltGuard and the Gulf Crop Library. EdgeSense v1 is partially built: its threshold safety layer runs on the pod today, and TinyML anomaly screening is still to come. Each carries its status on the Intelligence page. DewBrief is deferred to the pilot phase and isn't part of this build.

Will the dashboard be available in Arabic?

Yes. The Arabic UI ships after a human review of every translation, not a raw machine translation left unchecked. DewBrief, a weekly bilingual digest, is planned for the pilot phase once translation quality is proven at that review standard.

Company

What's the story behind IrrigAims?

IrrigAims began as Renowave, a student company in Kuwait, and won the Best Social Impact Award and placed Top 3 at the INJAZ Kuwait National Company Competition 2025. AgroSense also holds a CREST Gold Award from the British Science Association: see About & team for the full story.

How do I get in touch?

Email info@irrigaims.com: every enquiry gets a personal reply, or use the contact form.

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