SHUKA 100% offline

Africa Deep Tech Challenge 2026 · Agriculture

The agronomist that never guesses.

Shuka answers maize, cassava, rice and tomato questions from real extension manuals — cited by page, entirely offline, on an ordinary 8 GB laptop. Where it has no source, it says so.

Grounded · 4 sources
Shuka diagnosing fall armyworm on maize, with four cited sources beside the answer
9 → 0dangerous answers, raw vs grounded
19.2 tok/sofficial contest profiler, CPU
1.39 GBpeak memory of a 7 GB budget
0 bytesnetwork traffic after install

The problem

Good advice runs out before the road does.

Nigeria fields roughly one agricultural extension worker for every few thousand farmers — against a recommended one per thousand. The advice gap decides yields, and it is widest exactly where farming happens: rural areas with weak or unaffordable connectivity, on low-end hardware.

The obvious modern fallback — ask an AI — assumes bandwidth, cloud subscriptions and payment rails most smallholders don't have. So Shuka is built for the people farmers already ask: extension workers, agro-dealers and cooperative offices. One offline laptop at a cooperative becomes an answer desk for a whole community — and over the cooperative's own Wi-Fi hotspot, phones in the room can use it too.

Why grounding is the product

Small language models are confident liars.

These are real answers the same 1-billion-parameter model gave when we let it speak unsupervised. Each one could cost a farmer a season.

Grow cassava from seeds and harvest in about 3 months

Cassava is grown from stem cuttings and needs 8–24 months. A farmer following this loses the planting season outright.

Dangerous

Plant 30 maize seeds per hole

Recommended practice is 2 per station. Thirty seeds per hole destroys the stand and wastes a season's seed money.

Dangerous

Striga is a fungal disease — apply fungicides

Striga is a parasitic weed. Fungicide spend is wasted and the infestation keeps spreading.

Dangerous

How it works

Every answer walks the same four steps.

STEP 01

Ask

A farmer's question, in plain language — diagnosis, planting calendars, input dosages.

STEP 02

Retrieve

On-device search over 1,308 passages from 8 license-verified manuals — FAO, IITA, CABI, IRRI. Milliseconds, no network.

STEP 03

Answer, cited

The model writes only from the retrieved passages. Every claim carries its manual and page number, like a printed bulletin.

STEP 04

Or refuse

No passage clears the relevance floor? The model is never invoked. Shuka says so and points to the extension office.

Not a chatbot

Built for the answer desk, not the chat window.

A cooperative's laptop serves a queue of people on market day. Shuka's features come from that queue.

Paper, on purpose

Printed answer sheets

One click formats the answer as a handout — question, advice, citations, date. The farmer leaves with something they keep, in the medium advice has always travelled here.

Institutional memory

The ledger

Every answered question is remembered on the laptop. A repeat — even reworded — is served from the ledger in under half a second instead of a fresh generation. Shuka gets faster the more the community asks it, and the record never leaves the machine.

Advice that travels

Copy as text

One tap turns the answer into plain text with its citations, ready to forward by WhatsApp or SMS — because that is how advice actually moves from the desk to the field.

The alternatives, honestly

What the answer desk has today, and what Shuka changes.

An honest comparison — each column wins somewhere
At the deskPrinted manuals aloneCloud AI chatbotShuka
Works without internetYesNoYes
Cost per questionFreeData + subscriptionFree after install
Finds the right page in secondsNo — browse 850 pagesYesYes
Names its manual and pageIt is the pageRarelyEvery answer
Refuses instead of guessingRarelyBy design
Breadth beyond four cropsWhatever is on the shelfVery broadNot yet

Shuka doesn't replace the manuals — it is the fastest honest index into them. And where a cloud chatbot is genuinely stronger today (breadth, languages), the comparison only applies where there's bandwidth and money to reach it.

Evidence

We graded ourselves adversarially — and published it.

30-question evaluation · Llama 3.2 1B · same model, twice
ConfigurationCorrectPartialWrongDangerous
Raw model09129
Shuka (grounded)171030
9 dangerous answers
become 0.

That is the entire argument for the architecture, measured — on our own published question set, graded against the corpus text.

The sources

Built on manuals agronomists already trust.

Shuka's knowledge is not scraped. It is eight published extension documents — about 850 pages from FAO, IITA, CABI and IRRI — each license-verified before indexing. Documents we couldn't clear stayed out, and we say which ones.

Run it

Three commands. Then unplug the internet.

$ npm install && bash download_model.sh
$ npm run setup
$ npm run serve # → http://localhost:4180

Any 8 GB laptop with an i5-class CPU is enough. Integrated graphics gets used when present. Setup instructions, community-Wi-Fi mode and a hardware FAQ are on the run page.