Agriculture and food production
Agritech
Technology applied to farming and its supply chain.
Agritech sells something nobody can touch before buying: an app, a platform, a sensor rig. The farmer, the estate manager and the buyer's sourcing head all put the question to an engine before they put it to a salesperson, and the reply names one platform with a reason attached. Being the platform it names is the opening.
Where the answer is being lost
Agritech gets shortlisted in an answer, long before the demo.
An estate manager under input cost pressure asks "Does variable rate fertiliser application actually pay back in India" and gets a straight answer: yes under these conditions, no under those, and here is who supplies it. He is not opening ten tabs. He is reading one paragraph that either names you or does not. The same happens when a plantation head checks what a sensor rig costs to run for a season. If your evidence lives in a pitch deck, the engine has nothing to cite, and the trial goes to the platform it could quote.
How we win this
The programme for agritech
The payer is not the user
In agritech the person searching often never pays. A farmer asks about irrigation timing; an input company or an FPO funds the service he uses. We write one set of pages for the operator in the field and another for the sponsor or sourcing head who signs, then link them so an engine can see the same company answers both.
Payback maths, published
Every platform here claims a yield gain. That is why claims no longer move anyone. We publish the arithmetic instead: what the rig costs, what it replaces, how many acres before it makes sense, what happens in a poor rainfall year. Trial numbers from a named district and soil type carry weight that a national average never will.
Compliance is the wedge
Export buyers and certification schemes now dictate what a grower must record and for how long. Those requirements generate specific, researched questions with narrow correct answers, and most of the sector answers them badly. We build the record-keeping, audit-trail and documentation pages properly, mark up the standards and schemes as entities, and let the compliance question pull the software enquiry behind it.
In the grower's language
Prescriptive advice carries liability, and an instruction in the wrong language is worth nothing to the person holding the spray lance. So written guidance stays conditional: what the reading means, what to check before acting, when to call an agronomist. Demonstration goes to video, where the spoken vernacular becomes a transcript an engine can read and quote back.
The mix that carries it
Content
Answer and comparison pages
Cost, process, eligibility and comparison pages built for direct extraction, not for a reader who scrolls.
Content
GEO blogs and authority content
The definitive written answer to the questions your buyers put to an engine, structured so it can be lifted and attributed.
Authority
Original data and benchmarks
Proprietary numbers, surveys and benchmarks — the most-cited asset class there is, because nobody else has them.
Foundation
Entity and schema engineering
Structured data and entity definition so engines know exactly what you are, where you operate, and what you are credible in.
Content
Video and YouTube
Video run as a primary AI source, for the dense, entity-rich transcripts models read and quote.
Authority
Digital public outreach
Earned mentions, trade coverage and third-party citations — the corroboration a model checks before it names you.
The constraint we work inside
Two things bound what we publish. Crop protection and animal health advice must stay inside the label and the recommended practice, so we write conditions rather than instructions. And nothing we publish will promise a price, a yield or a payback, because none of those are yours to guarantee and buyers here can tell.
Specialisations
4 total
The pitch is different for each one, because the buyer, the trigger and the rules on what may be published are different for each one. Open the one that is yours.
A cotton farmer three days out from an irrigation decision asks "When should I irrigate cotton based on this week's weather", and the engine answers him without ever mentioning your app.
The question deciding this today
“When should I irrigate cotton based on this week's weather”
- Who they sell to
- Farmers seeking digital guidance on what and when to grow and spray
- Who signs
- The farmer, or an agribusiness sponsoring the service
- What starts it
- Season planning, pest alert, weather event, input decision
- Cost of staying invisible
- Advice arriving after the decision was already made
Your advisory logic sits behind a login and a phone number. Outside it, the answer is assembled from generic extension material, a university bulletin written for a different state, and whatever a content farm scraped last year. None of it knows the soil moisture band or the week. Meanwhile the agribusiness that might fund your service is searching for who already reaches growers at scale, and finds three other names before yours. The farmer decides at the pump; the sponsor decides at the budget meeting.
What we would run
- 01GEO blogs and authority content
A stage-by-stage advisory library: irrigation scheduling for cotton by growth stage and rainfall band, sowing windows by district, and what a named weather event means for the fortnight of operations that follows it.
The farmer asks this before he opens an app, not after. It is the only moment where being the cited source and being the chosen service are the same thing.
- 02Video and YouTube
Short vernacular films shot with the agronomist at the plot, each with a full transcript and chaptered captions: reading a soil moisture meter, judging when a pest alert warrants a spray, what the advisory screen is telling you.
What you are actually selling is judgement, and judgement does not show up in a screenshot of a dashboard. Watching your agronomist stand in the plot and make the call is the only demonstration of advice quality that exists. It works on both buyers at once: the grower sees whether the call is sound, and the agribusiness weighing a sponsorship sees the person its money would put in front of its dealers.
- 03Answer and comparison pages
Pages built for the funder rather than the field: how a sponsored advisory programme is priced, what coverage by district and crop means in practice, how farmer data is handled, and what an input company gets back from it.
The money comes from the agribusiness or FPO funding the service, not from the field, and that buyer opens with a commercial question, not an agronomic one.
- 04Entity and schema engineering
Entity work that ties your service to the crops, districts, languages and advisory types it covers, so an engine can tell that a cotton irrigation answer and a maize sowing answer come from the same organisation.
Advisory content is fragmented by crop and by season. Without the entity binding it together, each page reads as an orphan and none of them builds your name.
What we would not recommend
- Reddit. Prescriptive spray and dose discussion in an open forum is a liability we will not create for you, and the audience there is not the grower you serve.
- Instagram. It reaches urban agri-enthusiasts, not the farmer making an irrigation call this week, and an engine cannot read it as an answer.
- Reviews and testimonials. App store ratings say nothing about whether advice suited a particular district, and efficacy testimony on inputs strays into regulated claim territory.
What a lead looks like
A growth lead at an input company writes after reading your sponsorship pricing page and your cotton irrigation series. She has a dealer network in three states, a kharif budget to place, and wants to know which districts you already cover and whether the advisory can carry her agronomists' recommendations.
What we measure
- Inclusion on crop-stage advisory questions
- Vernacular transcripts indexed by crop
- Sponsor pages cited in answers
- Enquiries from funders, not downloads
What changes
The first call stops being an introduction and becomes a scoping call. An agronomist asks for a strip trial on two named blocks, having worked out from your district trial table the acreage at which the kit stops making sense. A procurement manager at a processor wants your rejection and settlement terms confirmed against a contract he is drafting this week. An estate manager rings with an audit date and three seasons of paper records, asking what can be migrated before the auditor arrives. An input company's digital lead asks what it costs to carry her agronomists' recommendations into your advisory for a kharif dealer push. None of them is asking what the product is. They are asking whether it fits, and that is the conversation your team is good at.
Start here
See who gets named in agritech today
We put your buyers' real questions to the live models and come back with the businesses they name, the sources behind those answers, and the gap between that list and yours.