Everything after yield

Company thesis

AfterYield is the intelligence and transaction layer for everything that happens after agricultural yield.

Before yield, the objective is production. The farmer determines what gets produced.

After yield, the objective is allocation. AfterYield determines what happens to it next.

An allocation engine for the physical world.

AI isn't the product. AI is the technology that makes allocation possible at scale — because after yield, almost nothing is certain.

The deeper insight

Agriculture splits into two worlds. Before yield: seeds, inputs, farming, irrigation, crop management, harvesting. After yield: aggregation, quality & grading, processing, packaging, storage, logistics, financing, distribution, selling. The first has attracted enormous technology. The second remains fragmented — and that is where value is lost.

A farmer produces a crop worth $100 at harvest. The buyer pays $180.

Where did the $80 go? That's AfterYield.

Core insight

Yield is not the end of agriculture. It is the beginning of the largest coordination problem in agriculture.

Before Yield vs After Yield

Before Yield

Production

The farmer determines what gets produced.

After Yield

Allocation

AfterYield determines what happens to it next.

Our ultimate product is Allocation: Given all the agricultural yield that exists, where should it go, through whom, at what quality, at what price, and at what time?

Example transaction

Saudi buyer needs 20 tonnes of Grade A avocado next Tuesday.
Kenyan farmer has 10 tonnes available.
Between them: Quality, timing, aggregation, processing, cold chain, logistics, pricing and demand.

What our software determines

Where the supply is
How much is actually available
What quality it will be
Which suppliers are reliable
Which processors have capacity
Which logistics providers can move it
The expected delivered cost
Which combination can fulfill the order most reliably

The moat

Transactions → Data → Prediction → Better allocation → More transactions

A commodity trader's moat is relationships + capital + inventory. A logistics company's moat is physical infrastructure. A generic AI company's moat is hard to defend. AfterYield's moat is the allocation flywheel: a proprietary dataset around yield × quality × time × location × processing × logistics × buyer × price × outcome.

Learning loop

Farmer → Yield → Quality → Processing → Logistics → Buyer → Price → Outcome

More transactions create better intelligence. Better intelligence creates better fulfillment. Better fulfillment attracts more transactions.

AI thesis

A probability engine around physical agricultural supply.

Farmer has 10 tonnes.

Farmer has an 87% probability of producing 8.6 saleable tonnes of Grade A/B product between September 4–8, with an expected landed cost in Medina of X.

Uncertain agricultural yield becomes predictable commercial supply.

Business model

Primary: Transaction fee when we successfully connect and coordinate supply with demand.
Secondary: Procurement intelligence, quality verification, logistics orchestration, financing, and market data.
Economics: Transactions and GMV — not inventory or physical assets.

Wedge

East African agricultural supply → Saudi demand

Small number of buyers, one high-frequency commodity, manually solving transactions before automating repeated workflows.

Vision

Today

AfterYield connects African yield to Saudi demand.

Tomorrow

AfterYield connects agricultural yield to demand across the Gulf.

Eventually

AfterYield becomes the global transaction and intelligence layer for what happens after yield.

Founder pitch

We're building AfterYield. Agriculture has gotten very good at producing yield, but everything after yield is still incredibly fragmented. Once a crop is harvested, nobody really knows where it should go, what its true quality is, who can process it, how to move it, or which buyer will pay the best risk-adjusted price. AfterYield is the intelligence and transaction layer for everything after yield. We don't own farms, trucks, warehouses or inventory. We connect the fragmented assets that already exist and use AI to determine how to move each unit of supply to the right buyer. We start with East African agriculture into Saudi Arabia. Our insight is simple: the physical infrastructure already exists. What's missing is the intelligence layer that coordinates it.

Brand

“We call it AfterYield because yield is where the traditional agricultural supply chain ends. We think it's where the interesting part begins.”

“The farmer creates yield. AfterYield creates value from what happens next.”