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Lacuna Fund is the rare AI funder whose entire product is data rather than models: it disburses funds to institutions to create, expand and maintain labelled datasets that fill gaps and reduce bias in machine learning for low- and middle-income contexts globally.
That focus makes it the natural home for work that has no route into a conventional AI grant - a labelled corpus for a low-resource language, an annotated agricultural imagery set for a specific region, a health dataset that does not exist anywhere in a usable form.
Past calls have covered natural language processing for low-resource languages and cultures in Africa and Latin America, antimicrobial resistance in Africa, Latin America and South and Southeast Asia, agriculture in sub-Saharan Africa, climate and energy, climate and health, sexual, reproductive and maternal health and rights, and climate and forests.
The eligibility structure is what distinguishes it from a standard research call and is worth reading closely: applicants must be a non-profit entity, research institution, for-profit social enterprise, or a team of such organisations, and individuals must apply through an institutional sponsor - but crucially the applicant must be headquartered in, or hold a substantial partnership in, the country or region where the data will be collected.
That requirement is a deliberate check on extractive data practices and it disqualifies a Northern institution proposing to build a Southern dataset without a genuine local lead. Budgets run USD 20,000-100,000 for small and medium projects and up to USD 500,000 for large ones, and the Fund offers a community platform, searchable directory and mentorship to help applicants form partnerships before submitting.
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Or search similar grants →According to the current listing, eligibility includes: Applicants must be a non-profit entity, research institution, for-profit social enterprise, or a team of such organisations; individuals must apply through an institutional sponsor. Applicants must be headquartered in, or have a substantial partnership in, the country or region where the data will be collected. Proposals must support the creation, expansion and/or maintenance of labelled datasets that fill gaps and reduce bias in machine learning of high social value in low- and middle-income contexts. Proposed budgets are anticipated in the range of USD 20,000-100,000 for small to medium-sized projects and up to USD 500,000 for large, complex projects. The Fund issues thematic calls rather than running a single continuous competition; past themes have included natural language processing for low-resource languages in Africa and Latin America, antimicrobial resistance, agriculture in sub-Saharan Africa, climate and energy, climate and health, sexual, reproductive and maternal health and rights, and climate and forests. Support for partnership formation is offered through a community platform, a searchable community directory and a mentorship programme. The most recent calls verifiable in the material reviewed had deadlines in 2024, and no currently open call could be confirmed. Applicants must check the open requests for proposals section at lacunafund.org/apply and confirm current themes, budget ranges, eligibility and deadlines, or contact secretariat@lacunafund.org, before preparing a submission. Confirm the full requirements in the official notice before applying.
The current listing shows proposed budgets are anticipated in the range of USD 20,000 to 100,000 for small to medium-sized projects, and as much as USD 500,000 for large, complex projects. amount_min of 20,000 and amount_max of 500,000 reflect that published guidance. These are budget expectations communicated to applicants rather than hard award ceilings, and the applicable range varies by individual call. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Lacuna Fund Calls for Proposals to Create, Expand and Maintain Labelled Machine Learning Datasets for Equitable AI in Low- and Middle-Income Contexts is funded by Lacuna Fund (a collaborative funder initiative supporting labelled ML datasets in low- and middle-income countries). 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.
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