Demand Intelligence Layer

Stop carrying
the wrong stock.
Start knowing
what's coming.

Vektor is a demand intelligence and agronomist workflow platform built for mid-size agri-input distributors. Predictive stocking, field intelligence, and real-time sell-through — three layers that compound on each other.

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220M+Soil Health Card records
10mSentinel-2 resolution
₹5–18CrTarget distributor revenue
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The Problem

Every stocking decision made on gut and last year's history.

A district-level distributor in Nashik or Ludhiana is sitting on ₹3–6 crore of inventory. Bags of DAP stacked to the ceiling. Pesticide bottles with shelf lives ticking down. His sales rep told him to load up on chlorpyrifos. He did. The pest pressure didn't come. Half those bottles expired. Meanwhile, three weeks into kharif, every farmer suddenly needed emamectin benzoate — and he ran out in 11 days, turning away 14 of his own retailers. Some didn't come back.

At dinner, he isn't complaining about "supply chain inefficiency." He's complaining about this specific decision that cost him ₹18 lakh.

₹18L
Written off in a single season — one wrong stocking call on chlorpyrifos, pest pressure never came
14
Retailers turned away at peak demand. Some moved permanently to the competitor two talukas over
7 yrs
Institutional knowledge that walked out the door when his best agronomist quit — relationships to 200 farmers, gone
The Platform

Three layers that compound on each other.

Each layer makes the next one stronger. Together they build an intelligence advantage no distributor outside the network can replicate.

01
Stocking Engine
Predictive Stocking Intelligence
+

Satellite-derived crop classification overlaid on your district, updated fortnightly using free Sentinel-2 imagery. Vektor knows that cotton acreage in Osmanabad taluka is 18% higher than last year. It cross-references that with NCIPM pest outbreak alerts, five years of your own sales history, and current weather forecasts — then generates a specific, dated, actioned recommendation.

"In the third week of July, demand for emamectin benzoate will likely spike 40–60% above your baseline. Your current inventory covers 19 days of projected demand. Recommended top-up: 340 units. Earliest recommended order date: June 28."
02
Agronomist App
Field Intelligence Platform
+

Your field agronomist walks into a farm already knowing the soil health card data for that plot, the last three crop cycles, every previous recommendation, and whether those products were purchased. In the field, he photographs a damaged plant. Vektor's vision model identifies it — "Likely tobacco caterpillar — 84% confidence, cross-referenced with 3 nearby farms that reported the same in the past 10 days" — and generates a digital recommendation with products pulled directly from your current inventory. One tap to the farmer's WhatsApp. GPS-tagged. Crop-observed. Logged permanently.

When your agronomist quits, his entire history of farm visits, crop observations, and recommendations stays in Vektor. His replacement walks in on Day 1 with seven years of institutional knowledge already loaded.
03
Sell-Through Network
Retailer Intelligence Layer
+

A lightweight WhatsApp-based daily stock report from your retailers — 2 minutes to fill out. When a retailer in Latur starts reporting unusual demand for a fungicide three weeks before it typically peaks, Vektor flags it. When three retailers in the same taluka run out of the same product on the same day, you get an alert and a suggested emergency warehouse transfer before it becomes a lost sale. Vektor also calculates a seasonal credit risk score for each retailer — because a cotton retailer in Vidarbha during drought-extended kharif is not the same credit risk as the same retailer during a good monsoon year.

Real-time sell-through data from the retail level — the most honest demand signal in the chain. And it only exists inside Vektor.
Season Prep Brief

Every 15 days, a procurement intelligence report for your territory.

Not a dashboard with charts. A brief that reads like an intelligence report — crop mix shifts, emerging pest pressures, expected SKU velocity by taluka, and a flagged list of products you're carrying too much of.

Your procurement decisions go from gut + history to data + early signal.

Kharif 2026 — Season Prep Brief ● Live
Osmanabad
Latur
Solapur
FAW Activity Detected — 3 clusters
Stocking Recommendation — Emamectin Benzoate
Cotton acreage ↑22% + early FAW signals across 3 clusters + 5yr demand data → projected spike 55% above kharif baseline, weeks 3–5 of July. Current stock covers 14 days at peak velocity.
420units recommended
Why Now

Three things that weren't true five years ago.

Sentinel-2 at 10-metre resolution — free.
Plot-level crop classification across an entire district using public satellite imagery. No proprietary contracts. Combined with India's Soil Health Card database — 220M+ records, now partially API-accessible — this is a ground truth layer about what's growing and what the soil needs that has never existed in usable form.
Vision models that identify pests from photographs.
Large vision models can now identify crop pests and diseases from field photographs with enough accuracy for a domain-knowledgeable agronomist to validate in 10 seconds. That collapses the bottleneck from "bring a sample to the lab" to "photograph it in the field." The speed difference is the difference between a timely recommendation and a missed sale.
WhatsApp Business API for zero-friction data collection.
Data collection pipelines built into communication infrastructure farmers and retailers already use daily. No behaviour change. No app downloads at the retailer or farmer end. The daily stock report that powers Vektor's sell-through intelligence runs entirely in the channel where retailers are already operating.
The Moment It Clicks

His own field team had been generating intelligence he never had access to.

What happens when a procurement manager sits down with the Kharif 2026 Season Prep Brief for the first time. Not a demo. The real thing.

1
Opening the Brief
He was expecting a slide with some charts. Vektor shows him his district on a map. He clicks on Osmanabad taluka. Satellite crop classification from the past 30 days. Cotton acreage: up 22% vs last season.
2
The Pest Layer
Six farm observations from his own agronomists — logged in the field over the past 18 days — show early fall armyworm activity in three clusters. The system cross-references with NCIPM data showing the same pest moving northward from Karnataka.
3
The Stocking Call
Emamectin benzoate demand projected to spike 55% above baseline in weeks 3–5 of July. Current stock covers 14 days. Recommended top-up: 420 units. Order by June 28.
!
The Realisation
"Hold on. The part about fall armyworm — my sales rep hasn't even called me about this yet. How does it know?"

Vektor shows him the field app log. His agronomist Suresh was in Latur on the 14th. He photographed a damaged cotton plant. The app flagged FAW at 79% confidence. Suresh confirmed it. The system connected it to two more observations from the same cluster — three days before Suresh filed his weekly report.

"Can we go live before June?"

— Procurement Manager, Maharashtra Distributor
After seeing the Kharif 2026 Season Prep Brief

The Math He Was Doing
Last kharif, he ran out of the same product and turned away ₹11 lakh of orders in 8 days. Vektor would have given him this signal two weeks before his rep mentioned it and three weeks before his competitor noticed the outbreak. The question wasn't whether Vektor was worth it. It was how quickly he could get it running.
Why It's Hard to Copy

The satellite data is public. The moat is what gets built on top of it.

01
Proprietary Ground-Truth Dataset
Geo-tagged crop observations, pest sightings, soil amendments made, and product responses logged by the agronomist app across thousands of farm visits per year. After two seasons, a distributor on Vektor has a farm-level knowledge map of their territory that no satellite, no government portal, and no competitor can replicate from outside.
02
Retailer Sell-Through Network
Once a distributor has 80 retailers reporting daily stock movement into Vektor, that real-time demand signal is the most accurate demand predictor in the region — and it only exists inside Vektor. When a distributor leaves, they lose all of that history, all those crop observations, and all that predictive accuracy. The switching cost is genuinely brutal, and it compounds every season.
03
Manufacturer Network Effects
Once manufacturers plug their demand planning into Vektor to get distributor-level sell-through data, the distributor on Vektor becomes a preferred commercial partner — better allocation, earlier price signals, priority stock during shortages. Leaving Vektor means leaving that commercial advantage, not just the software.
Expansion Logic

Growth that spreads in three directions simultaneously.

Upward
Manufacturers want the data.
The manufacturer above the distributor gets real-time sell-through and crop intelligence from the ground level for the first time. They'll pay for it — and start subsidising Vektor subscriptions for their distributor network to get it. Top-down adoption funded by the supply chain itself.
Horizontal
The product works better at scale.
Once 8–10 distributors in a district are using Vektor, pest outbreak alerts and crop mapping get dramatically more accurate — more agronomist observation points feeding the model. Distributors on the platform get demonstrably better forecasts. The gap between insiders and outsiders widens every season.
Lateral
A second revenue line from the data itself.
State agriculture departments and agri-input manufacturers — UPL, Bayer, PI Industries, Coromandel — eventually want access to the aggregated, anonymised crop and pest intelligence Vektor is sitting on. No additional fieldwork required. The data is already being generated by the existing workflows.
First Customer

The distributor who just had a bad season.

A district-level agri-input distributor in Maharashtra, Punjab, or Telangana doing ₹5–18 crore in annual revenue. Employing 3–6 field agronomists. Managing 80–150 retailers across 3–5 talukas. He just over-stocked something that expired, or ran out of something at peak demand. He's watching a new generic competitor start undercutting him on commodity fertilizers.

He can't compete on price on urea and DAP. His only defensible edge is being smarter than the next distributor — knowing earlier, stocking better, having an agronomy team that actually knows the farms in his territory. Vektor is that edge — and it pays for itself the first time it saves him from one bad stocking call.

₹5–18Cr
Annual revenue
3–6
Field agronomists
80–150
Retailers in network
3–5
Talukas covered