The $600 bet that information could fix African agriculture

Hey, Hannatu here 👋

What would you do with $600 and a dream? 

If you're anything like me, you're already halfway to the salon. 

But Alloysius Attah and Emmanuel Addai had a different idea. 

They decided to give African farmers something nobody had consistently given them before.

Information.

That was 2014. They were in Ghana. They had $600 and one observation that wouldn't leave them alone: farmers in Ghana were working so hard but earning very little. 

Attah knew this firsthand. Growing up in the Volta Region, he spent years helping his aunt farm. 

"Farmers wanted to make money from their hard work," he says in an interview, "yet much of the support available didn’t do much." 

And he was right. The problem was never that farmers weren't working hard enough. It was that they were working hard in the dark.

Last to know what the weather would do before they planted. 

Last to know what buyers wanted before they harvested. 

Last to know what their produce was worth before they sold it.

That information gap has a price tag. 

About 85% of smallholder farmers lack connectivity to lucrative markets, according to IFAD. In Kenya, small-scale maize farmers sell to middlemen at a loss of up to 40%, not because of bad harvests, but because they didn't know what the market was paying. 

Simply providing pest alerts to farmers across Ghana, Kenya, Malawi, and Zambia has increased yields and income by about 26%. The information existed. It just wasn't reaching the farmer.

Two people looked at all of that and decided information was the missing input. Then they tried to deliver it, and immediately ran into a wall.

The original plan was an SMS platform. 

Farmers would send information about their farms, and the system would send back soil recommendations, input connections, and market prices. 

It was clean, simple, and logical. Right?

Then they took it to the farmers. Even bragged to the extension workers that their tool might replace them.

Many farmers could speak their local languages, but couldn't read or write them. So the SMS platform was almost useless to them.

That humbling recalibration took them back to the drawing board where they built what has now become Darli AI, an AI tool that now communicates in 27 African languages through voice. 

Farmers get weather forecasts, agronomic advice, and market prices delivered in their languages. Via audio. 

"This isn't technology simply imposed upon farmers and extension agents," co-founder Emmanuel Addai said. "It's designed with them in mind, to answer their needs."

Which raises the obvious question: what does that actually change for a farmer?

Farmerline's core product is intelligence. Information, delivered at the right time, in the right language, to the right farmer.

Here's what that looks like in practice.

A farmer who knows tomorrow's weather doesn't plant the day before a flood. 

A farmer who knows what a buyer wants before the season starts plants the right crop instead of guessing and hoping. 

A farmer who knows what their produce is worth before they walk to the market doesn't get robbed by the first middleman they meet.

Maize prices in African markets swing by an average of 33% between harvest and lean season, two to three times more than in global markets. 

That gap exists because farmers sell at harvest when everyone else is selling and prices are lowest. 

They don't do this because they want to. 

They do it because they have no storage, need cash immediately, and aren’t sure what prices will look like in three months.

Knowing when to sell, and having the means to wait, can be the difference between a farmer who only breaks even and one who makes enough profit to grow. Most farmers have neither.

Farmerline closes that gap. 

Before farmers plant, their platform tells them what buyers want, how much they want, and what quality standards are required. Buyers send approximately $200 million worth of purchase requests through the platform annually. 

So the demand is there. The farmers also are there. Farmerline is the data sitting between them.

But market information was only half the problem. The other half was money, and that one was just as interesting.

Only about 5% of rural households in Ghana have access to credit for agricultural financing. 

Those who do face high interest rates and short repayment periods. 

For most smallholder farmers, formal credit is inaccessible. And it’s not always because they are bad borrowers, but because lenders have no way to assess them.

Farmerline noticed that farmers were already lending money to one another.

But unlike traditional banks and other formal institutions that used credit scores or bank statements, they were leveraging harvest history, community reputation, and local knowledge. 

That became their own form of credit assessment.

That insight became Farmerline's Open Finance platform. 

Instead of asking banks to take a leap of faith by extending traditional credit to farmers with no formal financial history, Open Finance uses alternative data like yield records, farm performance, climate information, and field monitoring to build credit profiles. 

The data was always there. It just needed someone to make it legible to the people with money to lend.

Which is, at its core, exactly what Farmerline does. For markets, for lenders, for input suppliers, for everyone in the chain: they make the invisible visible. 

And then they license that infrastructure to the people who need it most.

Farmerline didn't try to reach millions of farmers directly. 

They licensed their intelligence infrastructure to the companies and organisations already working with farmers. This included the input suppliers, financial institutions, agricultural extension services, and development organisations.

Their logic made sense. 

Getting a farmer to adopt a new system is hard. Getting a fertiliser company that already sells to that farmer to use a better system is easier. And when the intelligence is embedded in a transaction the farmer is already making, adoption happens automatically.

So far, they’ve raised $6.4 million in a Pre-Series A round. Alongside that came $6.5 million in debt financing. 

So far, over 60 partners across Africa, Asia, and Latin America now use their platform for farmer profiling, input recommendations, payment processing, and supply chain traceability.  About 2.3 million farmers have been reached.

Each partner brought their own farmer relationships. Farmerline brought the intelligence to make those relationships more productive.

All of that from $600 and a single question: what does a farmer actually need?

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Cheers,