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The AI4Good AgriTech Farmer Solutions challenge, run under the Moonshots for Development Open Innovation Challenge, funds digital tools that improve the accountability, efficiency and reach of agricultural and rural advisory services for smallholder farmers and rural communities. It offers up to 360,000 US dollars per team across four progressive phases.
The problem it targets is specific and well documented: agricultural extension services in much of the Global South are overwhelmed, with advisor-to-farmer ratios that make individualised guidance impossible, and the challenge is premised on AI being able to close part of that gap.
Solutions embedding artificial intelligence are strongly encouraged, with the challenge highlighting AI's potential to accelerate data interpretation, improve prediction and modelling, and personalise advisory services, and framing the work explicitly as AI for Good.
Eligible solution types include data-driven extension platforms, automated decision-support systems and tools that strengthen institutional capacity, alongside the challenge's stated focus on Digital Extension for Accountable Service Delivery.
The emphasis on accountability is worth noting, since it pushes applicants toward solutions that make advisory delivery verifiable rather than merely scalable, a framing that distinguishes this from most AgTech funding. The challenge is open to startups, and the four-phase structure means teams can enter without the institutional apparatus a conventional grant requires.
No deadline is recorded here because the published deadline of 30 March 2026 has passed; the challenge format suggests subsequent rounds are likely.
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Or search similar grants →According to the current listing, eligibility includes: The challenge is aimed at startups with digital tools that enhance the accountability, efficiency and reach of agricultural and rural advisory services for smallholder farmers and rural communities, so the applicant profile is a venture or team with a product rather than a research group with a hypothesis. Eligible solution types are described as data-driven extension platforms, automated decision-support systems and institutional capacity strengthening tools, with the challenge's stated priority being Digital Extension for Accountable Service Delivery. Solutions embedding artificial intelligence are strongly encouraged rather than strictly required, so a strong non-AI digital solution is not excluded, but AI-centred proposals are explicitly favoured and the challenge is framed around AI for Good. Geographic eligibility is not explicitly specified in the published materials, though the challenge references developing countries and Sub-Saharan Africa as the contexts where extension services are most strained, so applicants should confirm whether their target geography and country of registration qualify before applying. The four-phase progressive structure means selection is staged and continued funding is contingent on advancing between phases; teams should understand the per-phase criteria and disbursement amounts, which are not published, before committing resources. The published deadline was 30 March 2026, which has passed, and no deadline is recorded here. Prospective applicants should consult the Moonshots for Development challenge pages for current or successor rounds and verify the funder structure, since open innovation challenges of this type are frequently run in partnership with development agencies whose own eligibility rules may apply. Confirm the full requirements in the official notice before applying.
The current listing shows the challenge offers up to 360,000 US dollars per team across four progressive phases, and because that is published as a single per-team ceiling without a stated floor, amount_min and amount_max are both recorded as 360,000. The per-phase breakdown is not published, which is the most consequential gap for planning purposes. A four-phase progressive structure means the 360,000-dollar figure is a cumulative maximum available only to a team that advances through every stage, not an initial award, and in challenges of this design the early phases typically disburse a small fraction of the total while the bulk is contingent on reaching final-stage selection. Applicants should therefore model the realistic expected value as substantially below 360,000 dollars and should not plan hiring or infrastructure commitments against the headline figure. The progressive structure does have a compensating advantage: it lowers the barrier to entry, since teams can compete for the first phase without the institutional overhead a conventional grant application requires, and attrition risk is borne stage by stage rather than all at once. Because the challenge targets solutions for smallholder farmers and rural advisory services in developing-country contexts, applicants should also factor in field deployment and user-validation costs, which are typically underestimated in digital advisory projects and which the later phases are presumably intended to cover. Teams should confirm the current phase amounts and disbursement terms with the organisers before committing. Verify award ceilings, matching requirements, and allowable costs in the official notice.
AI4Good AgriTech Farmer Solutions Open Innovation Challenge for AI-Embedded Digital Agricultural and Rural Advisory Services for Smallholder Farmers is funded by Moonshots for Development (M4D) Open Innovation Challenge. Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
The Climate Change AI Innovation Grants program supports projects that address research and deployment challenges in climate change mitigation, adaptation, and climate science by leveraging AI and machine learning, while also creating publicly available datasets and tools to catalyze further work. The program enables key partnerships that accelerate the research-to-deployment cycle, creating synergies between academic researchers, nonprofits, startups and other companies, and governmental or intergovernmental organizations. Funded by the Quadrature Climate Foundation, Schmidt Futures, and Google DeepMind, with Future Earth serving as fiscal sponsor, this is one of the few dedicated grant programs specifically targeting the intersection of AI/ML and climate change. Projects typically involve climate modeling, weather prediction, emissions monitoring, energy optimization, biodiversity monitoring, and other environmental applications of machine learning. The 2026 competition opens with a full proposal deadline of September 15, 2026. The program has grown steadily since its inception, funding 23 projects to date across diverse climate domains and geographies.
The Climate Change AI Innovation Grants program supports catalytic projects using AI and machine learning for climate action, funding research and deployment challenges in climate change mitigation, adaptation, and climate science. Projects must create publicly available datasets and tools as digital public goods, and release open-source code. The program builds partnerships between academic researchers, non-profits, startups, companies, and governmental organizations to accelerate the research-to-deployment cycle. Past funded projects span climate modeling, emissions monitoring, renewable energy optimization, and disaster prediction across all continents.
The Halcyon Africa Innovation in Agriculture and Food Security Accelerator supports early-stage, impact-driven ventures across Sub-Saharan Africa that are strengthening agriculture and food systems through market-based solutions. The 2027 cohort is open for applications until 23 October 2026. Technology is explicitly central to the scope: the programme welcomes tech-enabled agriculture and food security solutions across ten priority sectors, including agricultural data platforms, digital extension services, precision agriculture tools and agri-fintech innovations, all areas where AI and machine learning are typically the core of a competitive product. Each selected venture receives a 10,000 US dollar equity-free stipend and 10,000 dollars in Amazon Web Services credits, together with access to Halcyon's community of more than 650 founders, professional advisory support, expert-led workshops covering leadership development, capital strategy and product-market fit, and investor networking. The format is hybrid, combining virtual sessions with in-person residencies in Accra, Ghana and Nairobi, Kenya. What distinguishes this from most AI-for-agriculture funding is the applicant profile: it targets commercial ventures with working products and demonstrated traction rather than research teams, requiring paid-pilot or post-revenue stage with a working minimum viable product. For African AgTech founders building AI-driven advisory, monitoring or decision-support tools who have passed the prototype stage and need capital strategy support and investor access more than research funding, this is a well-matched and currently open opportunity.
The Citi Foundation's fourth Global Innovation Challenge commits $25 million in restricted grants — 50 awards of $500,000 — to organizations preparing low-income youth for an AI-shaped economy. The letter of inquiry closes October 6, 2026 at 12:00 p.m. ET, full applications land in December, grant terms start no sooner than June 1, 2027, and the cash splits across 2027 and 2028. Here is the eligibility math, the two rules that eliminate most applicants, and why this is a planning instrument, not budget relief.
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