For years, agritech in emerging markets was sold on a seductive premise: agriculture could leapfrog missing infrastructure the same way mobile phones helped consumers bypass fixed-line banking and communications. Build a marketplace, onboard farmers, connect buyers, add a layer of data, and scale would follow.
That story is now colliding with the harder reality of rural Asia. The “AgTech Investment in Emerging Markets 2025” report prepared by AgBase, Briter, and Mercy Corps, has found that fragmented farm supply chains cannot be fixed by software alone when produce still moves across poor roads, storage is unreliable, cold chains are patchy, and quality control depends on human judgement at the farmgate.
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The funding correction after 2023 has made that weakness harder to ignore. As capital became more selective, many “venture bets” built on rapid user growth and thin digital coordination started to look fragile. In their place, investors and founders are being forced to consider “system bets”: businesses that may be slower and messier to build, but which are grounded in logistics, trust, repayment behaviour, and actual control over supply.
In Southeast Asia, where agriculture remains central to employment and food security, this distinction matters. Indonesia’s startup correction offered an early warning. Growth-at-all-costs models, often backed by generalist venture capital, struggled when operational controls and unit economics did not keep pace with expansion. In agriculture, that gap is even more punishing because the offline world does not bend easily to digital ambition.
The infrastructure problem software cannot hide
The core challenge is simple: in many emerging markets, infrastructure is not a support layer. It is the bottleneck.
A startup that wants to aggregate farmers, sell inputs, finance planting, or connect produce to buyers often discovers that it must also solve for transport, warehousing, grading, traceability, and sometimes even power reliability. These are not side problems. They determine whether the platform can deliver on time, preserve quality, reduce waste, and get paid.
This is why the clean distinction between asset-light and asset-heavy models is becoming less useful. Asset-light platforms, built mainly around transactions and coordination, can work in more mature markets where roads, storage, logistics providers, and buyer standards are already functional. But in weaker ecosystems, the same model often has little control over the messy parts of the chain that decide whether a transaction succeeds.
The lesson from markets such as Nigeria is relevant for Asian founders. Basic infrastructure cannot be leapfrogged. Digital tools may improve visibility and coordination, but they cannot make produce travel faster on broken roads or keep perishables fresh without cold storage. Before data rails can generate value, “hard rails” — storage, logistics, fulfilment centres, and quality systems — often need to be built or tightly controlled.
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This does not mean every agritech startup must own trucks and warehouses. But it does mean founders need a serious answer to who controls the physical movement of goods and how quality is verified. In agriculture, trust is not created by an app interface. It is earned through repeated offline execution.
The rise of the phygital model
That is why the “phygital” model, combining physical infrastructure with digital systems, has shifted from being a fashionable term to a practical requirement.
The digital layer still matters. It can capture farmer data, manage payments, monitor supply, forecast demand, and support credit scoring. But the human and physical layers are just as important. Field agents remain essential in smallholder markets because they translate technology into trust. They help farmers understand products, verify crop conditions, manage service delivery, and reduce the perceived risk of engaging with a platform.
This is particularly important in Southeast Asia, where smallholders often operate on thin margins and rely on local relationships. A farmer in rural Java, Mindanao, or the Mekong Delta may not adopt a service simply because it is cheaper or more efficient on paper. Adoption depends on whether the provider is known, whether payment terms are credible, and whether the platform shows up when something goes wrong.
African examples underline the point. ThriveAgric in Nigeria and Twiga Foods in Kenya have both demonstrated that agricultural platforms often need direct involvement in fulfilment, logistics, and buyer relationships. Kenya also offers a cautionary tale: donor-backed pilots can validate ideas without proving commercial durability. Without the physical layer, many projects remain trapped as pilots rather than becoming scalable businesses.
For emerging Asia, the implication is clear. The winners are unlikely to be pure apps. They will be companies that use software to coordinate a deeper operating system across inputs, finance, logistics, and market access.
Why single-point apps struggle
The era of the standalone crop advisory app is fading. Advice alone is hard to monetise, especially when farmers are price-sensitive and customer acquisition is expensive. A platform that tells a farmer what to plant or when to spray may create value, but it often struggles to capture enough of that value to build a durable business.
The stronger model is bundled. A platform that provides quality inputs, links farmers to buyers, embeds financing, and captures transaction data becomes harder to replace. It also creates multiple revenue pools. Instead of charging farmers directly for every service, the platform can monetise downstream through processors, corporates, insurers, lenders, and buyers that care about traceability, reliable supply, water efficiency, and climate resilience.
This shift matters because the strongest economics in agritech often sit beyond the farmer. Corporates may pay for verified supply. Lenders may pay for better risk data. Buyers may pay a premium for predictable quality. Insurers may rely on platform data to price products more accurately.
When these services are integrated well, the results can be meaningful. Bundled platforms have reported repayment rates above 95 per cent and farmer income gains of 20-30 per cent. Those figures are not just impact claims. They point to the commercial logic of deeper integration: farmers stay because the platform solves several problems at once, while partners pay because the system reduces risk.
The capital stack has to change
The difficulty is that this kind of agritech does not fit neatly into traditional venture capital timelines. Building logistics networks, field operations, financing systems, and quality controls takes time. A five-to-seven-year fund horizon can push founders towards fast growth before the operating foundations are ready.
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That mismatch is becoming one of the sector’s central financing challenges. Agricultural infrastructure often needs patient capital, blended finance, working capital facilities, and strategic corporate participation alongside equity. Brazil offers one example of how an agritech ecosystem can scale when domestic debt markets and corporate venture arms complement startup funding. In other markets, concessional capital can help de-risk early infrastructure, before commercial investors fund growth.
For Southeast Asia, this is especially relevant as food security, climate adaptation and rural income become more urgent policy priorities. Governments and development finance institutions can help build public goods such as farmer registries, digital IDs, and climate data systems. But commercial startups still need disciplined models that can survive without permanent subsidy.
The next phase of agritech in emerging Asia will not be won by the company with the slickest dashboard. It will be won by those that understand the farm economy as a system: physical, financial, human, and digital.
The shift from clicks to bricks is not a retreat from technology. It is a recognition that technology only works when it is anchored in reality. In agriculture, that reality is muddy, fragmented, and deeply local. The companies that accept this early will have a better chance of building platforms that are not only scalable, but permanent.
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