Agriculture
Reference architecture for an agricultural advisory assistant – multilingual, multi-channel guidance grounded in agronomy, with weather-aware alerts, powered by the NAISH Hub.
A smallholder farmer wants advice over chat, voice, or IVR, in their own language; an extension agent supports many farmers from an app. This template shows an advisory assistant grounded in agronomy that also pushes timely alerts.
How it works
- Channels – farmers reach the advisor over chat, voice, or IVR; extension agents use an app.
- Gateway & consent – access, authentication, and consent first.
- AI advisory agent (+ skills) – reasons about the question and calls skills: the model for language, retrieval over agronomy knowledge, and the farmer-profile service for personalised advice.
- NAISH Hub – serves the models on GPU. Sovereign AI core.
- Data & dependencies – a vector store grounds advice, a farmer database personalises it, weather / GIS data informs alerts, and alerts fan out to messaging (IVR / SMS) through a queue.
Where the Hub adds value
- Local-language reach – Hub-served models advise in the farmer's language across low-bandwidth channels.
- Grounded, timely – retrieval ties advice to real agronomy; weather-aware alerts reach farmers before they need to act.
- Sovereignty – farmer data and models stay on national infrastructure; see Governance & Risk.
Reusable building blocks
| Layer | This template | Swap in for your context |
|---|---|---|
| Channels | Chat / voice / IVR + agent app | Any farmer or field channel |
| Agent + skills | Agronomy retrieval, profile, alerts | Crop / region-specific skills |
| Models (Hub) | Local-language advisory LLM | Domain-tuned models |
| Services | Profile, advisory / alerts | Whatever platforms the programme runs |
| Data | Farmer database + agronomy | Any governed agricultural source |
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