PowerPoint Presentation

2 Traditional vs. Alternative Funding Models. Funded by the European Union.

[Audio] Welcome to this module on Traditional versus Alternative Funding Models. Many digital agriculture solutions fail not because the technology is weak, but because the funding model does not match the nature of the innovation. Agriculture has historically relied on stable, asset-based financing—land, machinery, and infrastructure. Digital agriculture, however, introduces uncertainty: intangible assets like data and software, delayed returns, and new business models. The image of the puzzle piece labelled "funds" symbolises this mismatch. traditional funding models , such as public grants, subsidies, and bank loans , and alternative or non-traditional approaches that have emerged to address uncertainty, early risk, and adoption challenges. The goal is not to promote one model over another. Instead, the goal is to understand how different funding logics operate, when they are appropriate, and what their limitations are.

[Audio] "Traditional funding refers to financing mechanisms that are institutionally mature and widely embedded in agriculture and agri-food systems. Traditional funding models prioritise stability, predictability, and risk minimisation. Decisions are rule-based and rely heavily on asset-backed assessments, collateral, and proven cash flows. These models work very well when technologies, markets, and returns are known and when the goal is incremental improvement rather than experimentation. This is why banks, public funding schemes, established venture capital, and private equity have historically dominated agriculture finance.

[Audio] Agriculture has structural characteristics that naturally align with traditional funding. First, agriculture is capital intensive. Land, machinery, and infrastructure require large upfront investments with long lifespans, making collateral-based finance the default option. Second, farm income is highly volatile. Weather, biological risks, market prices, and geopolitical events create uncertainty, reinforcing a preference for predictable financing. Third, agriculture plays a strategic role in food security and rural livelihoods. This explains the strong involvement of public policy, subsidies, and stabilisation mechanisms. Finally, many agricultural investments have long cycles and low margins, which discourages risk-taking and favours conservative financing structures..

[Audio] Alternative—or non-traditional—funding refers to financial mechanisms outside conventional channels such as bank loans, government grants, and mainstream venture capital. These models are characterised by greater flexibility, higher risk tolerance, and often a participatory or mission-driven approach. In digital agriculture, alternative funding expands the financial toolbox, enabling projects to progress even when they don't meet the strict criteria of traditional funders. The green statement at the bottom is important: alternative funding does not replace traditional funding—it complements it, especially in early stages or novel use cases.

[Audio] At this point, we introduce a taxonomy of alternative funding models, grouped by their underlying logic rather than by individual instruments. We distinguish four main categories: Equity & outcome-oriented Non-dilutive & community-based Debt & risk-sharing Digital & experimental Each category responds to different innovation stages, risk profiles, and adoption challenges in digital agriculture. The specific instruments listed here will be explored further in later modules—this slide provides the conceptual map..

[Audio] Equity and outcome-oriented funding focuses on long-term value creation rather than short-term financial return. Capital is provided either as equity or linked to predefined outcomes—such as adoption rates, environmental impact, or social results. Investors are often actively involved in governance and strategy, and investment horizons tend to be longer than in traditional VC. However, this model requires clear and measurable impact metrics, and governance can become complex when multiple stakeholders are involved..

[Audio] Non-dilutive and community-based funding mobilises capital without transferring ownership or control. Funding often comes from collective participation, public engagement, or earned income, helping build early trust and legitimacy around digital solutions. These models are particularly effective for pilots, early adoption, and community-driven innovation. Their main limitation is scale—funding volumes are often modest, and strong communication and credibility are essential..

[Audio] Debt and risk-sharing models provide repayable financing while redistributing risk across multiple actors. This is achieved through guarantees, co-financing, or blended structures involving public and private actors. These mechanisms enable farmers and SMEs to invest in proven digital solutions, especially during scaling and deployment phases. However, they still require predictable cash flows and careful structuring—poor design can shift excessive risk onto end users..

[Audio] Digital and experimental funding models explore new ways of mobilising capital through digital platforms or novel governance structures. These models often operate on a pilot or small-scale basis and test new forms of participation, transparency, and coordination. While promising, they face regulatory uncertainty, unproven scalability, and a high dependence on user trust and digital maturity. As the closing statement notes, these models explore new funding logics for data-driven and platform-based agriculture, but they are not yet mainstream..

[Audio] This slide brings together everything we've discussed so far into a side-by-side comparison between traditional and alternative funding models, specifically in the context of digital agriculture. On the traditional funding side, risk is something to be minimised and controlled. Lenders and investors aim to protect capital by requiring strong collateral, proven cash flows, and low uncertainty. As a result, projects with high technological or market uncertainty are often avoided. In contrast, alternative funding starts from the assumption that risk is inherent to innovation. Instead of avoiding it, risk is managed or shared—through staged funding, guarantees, blended structures, or collective participation. Traditional funding relies heavily on tangible assets and validated business models. Land, machinery, infrastructure, and proven intellectual property are used to secure repayment or exit value. Alternative funding is more flexible. It can be based on intangible assets such as data, digital platforms, user networks, or expected future value—rather than physical collateral. This distinction is critical for digital agriculture, where value is often embedded in software, data, and services rather than equipment. Traditional funding tends to concentrate on late-stage or already proven solutions—either early research funded by public instruments or mature technologies ready for scale. Alternative funding, by contrast, is more willing to support early-stage and experimental innovation. This is particularly important for bridging the so-called "valley of death" between a prototype and commercial deployment, where many digital agriculture solutions struggle Traditional funders focus primarily on track record and financial metrics. Decisions are driven by compliance, financial projections, and historical performance indicators. Alternative funding broadens the evaluation lens. In addition to financial viability, decisions emphasise future potential, impact outcomes, and ecosystem relevance. This allows promising innovations to be supported even before they generate stable revenues. In traditional funding models, scalability is expected to be rapid, replicable, and market-driven, often prioritising growth speed over contextual adaptation. Alternative funding views scalability differently. It is understood as gradual and context-dependent, allowing solutions to evolve through local adoption, learning, and iteration before expanding more widely. This approach is often better aligned with the realities of agriculture, where local conditions matter..

[Audio] Many innovations work technically, but the funding model does not fit the nature of the innovation. First, digital agriculture creates value through intangible assets—data, software, analytics, services—while traditional finance still relies heavily on physical collateral. Second, adoption in agriculture is slow and cautious by nature, yet many funding models expect fast growth and quick returns. Third, successful pilots often demonstrate impact, but not bankability. This creates a gap between proof of concept and commercial finance. Finally, public funding frequently stops once the technology is developed, leaving no mechanism to support adoption, deployment, and scaling. The result is that risk is pushed downstream—often onto farmers—who are least able to absorb it..

[Audio] This slide introduces a key concept blended finance. Blended finance is not a funding instrument on its own. It is a way of structuring finance so that different actors take different levels of risk. Typically, public or catalytic capital is used first—to absorb early risk, provide guarantees, or co-finance pilots. This risk reduction then makes it possible for private finance—banks, investors, or alternative mechanisms—to enter later. In digital agriculture, blended finance is particularly powerful because it connects innovation funding with adoption funding, rather than treating them as separate worlds. In the next module, we will look at concrete blended mechanisms and how they work in practice..

[Audio] The key takeaway from this module is that alternative funding fundamentally expands what is considered "financeable." By recognizing future value, shared risk, mission outcomes, and collective participation, alternative models enable innovations that would otherwise remain unfunded. No single funding instrument fits the entire innovation lifecycle. Effective strategies combine instruments across stages, actors, and risk profiles. Funding models are not neutral. They shape which technologies are developed, which are adopted, and which never reach the field. In digital agriculture, innovation failure is often a financing failure — driven by gaps between development, adoption, and scaling capital. Traditional finance is structurally misaligned with many digital solutions, making alternative and blended models essential rather than optional..

CASE STUDIES. Funded by the European Union.

[Audio] Breedr, shown here, is a UK agri-tech startup providing a digital livestock management platform. What makes Breedr particularly relevant in this module is how it raised capital. Instead of relying solely on traditional venture capital or bank finance, Breedr used equity crowdfunding. In doing so, it invited its own farming community to become investors. The result was remarkable: more than €1.6 million raised in just 24 hours, largely from farmers and local stakeholders who already understood the problem the platform was solving. A critical point here is that investors were also end-users. This reduces information asymmetry, accelerates trust, and strengthens adoption. Funding and market validation happen simultaneously. From a digital agriculture perspective, this model works particularly well where solutions require behavioral change, user trust, and community buy-I, areas where traditional finance often struggles..

[Audio] Farmcrowdy originated in Nigeria as a digital platform connecting individual sponsors with farmers who lacked access to formal financial institutions such as banks or venture capital. In many emerging agricultural contexts, farmers are creditworthy in practice but invisible to traditional finance. The innovation here is not only financial, but organizational and digital. Through a mobile-based platform, urban professionals and individual investors could digitally "sponsor" specific farms. Their capital was used to finance concrete inputs — seeds, fertilisers, basic equipment, and advisory services — rather than business plans. Returns for sponsors were linked directly to agricultural output, not to equity exits or speculative growth. This makes the model closer to crowdlending or revenue-linked financing, adapted to agricultural cycles and risks. A key role of the platform was monitoring and transparency. Farmcrowdy used digital reporting, updates, and basic data tracking to reduce information asymmetry between sponsors and farmers — a critical barrier in traditional agricultural finance. From a digital agriculture perspective, this model demonstrates how technology can substitute for collateral. Instead of land titles or balance sheets, trust is built through data, traceability, and continuous visibility of farm performance..

[Audio] Omnivore is an impact-focused venture capital fund that invests in agri-tech, precision farming, and digital agriculture startups, primarily in emerging markets. At first glance, it may look similar to traditional venture capital — it invests equity, seeks scale, and expects financial returns. The key difference lies in how success is defined and how risk is interpreted. Omnivore is a financial-first impact investor, meaning it still targets market-rate returns, but it explicitly recognises that agriculture requires patient, mission-aligned capital. Returns are expected over longer time horizons, and investments are shaped by sector realities such as seasonality, adoption cycles, and farmer behaviour. Unlike conventional VC, where value creation is often measured primarily through rapid growth or exit potential, Omnivore evaluates performance through both financial metrics and impact outcomes. These outcomes include farmer income, climate resilience, emissions reduction, and sustainable land use — as illustrated on the right side of the slide. Importantly, the technologies Omnivore supports are not innovations. They typically include digital advisory platforms, precision agriculture tools, climate-smart farming systems, and data-driven services designed for small and medium-scale farmers. This places Omnivore squarely at the intersection of digital innovation and real-world agricultural impact. From a funding-model perspective, this case shows how impact investing stretches traditional equity logic. Risk is not eliminated, but it is reframed: success depends not only on market traction, but also on whether the solution delivers measurable value to farming systems and rural communities. This is why impact capital often plays a bridging role — filling gaps where traditional VC is too impatient and where public funding alone cannot scale solutions. In later modules, we will see how impact investors frequently combine their capital with grants, guarantees, or public instruments through blended finance structures..

thank you!. TALLHEDA has received funding from the European Union's Horizon Europe research and innovation programme under Grant Agreement No. 101136578. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency (REA). Neither the European Union nor the granting authority can be held responsible for them..

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