Lacuna Fund provides data scientists, researchers, and social entrepreneurs with the resources they need to either produce new labeled datasets to address an underserved population or problem, augment existing datasets to be more representative, or update old datasets to be more sustainable. All datasets produced will be locally developed and owned, and they will be openly accessible to the international community while adhering to best practices regarding ethics and privacy.


You can review a copy of RFP questions, including the prompt for the narrative portion of the proposal, under each RFP. When an RFP is open, proposals are accepted through the application portal.


Lacuna Fund aims to make its funding accessible to as many organizations as possible in the AI for social good space and cultivate capacity and emerging organizations in the field.  

To be eligible for funding, organizations must: 

  • Be either a non-profit entity, research institution, for-profit social enterprise, or a team of such organizations. Individuals must apply through an institutional sponsor. Partnerships are welcome but only the lead applicant will receive funds.
  • Have a mission supporting societal good, broadly defined.  
  • Have all necessary national or other approvals to conduct proposed research. The approval process may be conducted in parallel with grant application, if necessary. Approval costs, if any, are the responsibility of the applicant. 
  • Have the technical capacity to conduct dataset labeling, creation, expansion, and/or maintenance. 
  • Be sufficiently stable to ensure the sustainability of the dataset or have arrangements with an organization of sufficient stability. 

Selection Process

Lacuna Fund uses an open solicitation process, conducting requests for proposals (RFPs) for projects aligned with Fund goals in a particular domain on a fixed timeframe. In other words, we are not accepting proposals for every domain at all times, but when we are, solicitations are open to any applicant who meets the eligibility criteria. 

Initial screen: RFPs are generally open for 45 days or more. Proposals are submitted through an online portal. After the conclusion of an RFP, the Secretariat and partners perform an initial screen for qualifications and eligibility criteria.  

Panel review: Following the initial screen, a Technical Advisory Panel of domain experts review proposals based on selection criteria, then meet to make selections. Technical Advisory Panel members who review proposals for an RFP are not eligible to submit or collaborate on proposals for that call 

Notification and revisions: After the Technical Advisory Panel meets, the Secretariat will finalize selections or communicate any needed revisions to potential recipients. All communication and revisions will be finalized through the applicant portal.  

Post-award confirmationUpon notification of selection, recipients will be prompted to submit due diligence and financial information through the applicant portal. 

Potential grantees should not begin work until a contract has been signed. More details on expectations and support after a grantee begins work are available through the portal for current grantees. 

Open Funding Opportunities

If an open funding opportunity below does not match your substantive focus, please join our mailing list at the bottom of this page to receive updates as new EOIs/RFPs are released.

16 June 2021 – 27 July 2021

Expressions of Interest: Machine Learning Datasets for Better Healthcare Outcomes

The Lacuna Fund Secretariat has extended the due date for Expressions of Interest (EOIs) to its call for proposals to unlock, create, aggregate, and/or improve labeled datasets that can support more equitable healthcare outcomes. EOIs are now due 27 July 2021 by end of day (6:00 pm) US Pacific Time.

Additionally, we have modified the question-and-answer period to provide extra time for additional questions related to the EOI. Please submit any additional questions by 16 July (end of day). Responses to those questions will be provided on 20 July (end of day). All questions related to the EOI should be submitted to with “Equity & Health 2021 Question” in the subject line.

Applications for open funding opportunities are only accepted through the applicant portal. The portal requires you to create an account to access and manage your application. More information on how to create an account and access the portal can be found on SurveyMonkey Apply’s website.

Lacuna Fund seeks Expressions of Interest (EOI) from organizations interested in responding to a call for proposals to unlock, create, aggregate, and/or improve labeled datasets that can support more equitable healthcare outcomes.

A full copy of the EOI solicitation, including more details on potential areas of funding, eligibility, and selection criteria, is here.  

20 July – the Updated Question & Answer file is available here.

Applications are accepted through the application portal here.


  • RFP Posted Publicly on Lacuna Fund Website: 16 June 2021
  • Question and Answer Deadline: 16 July 2021
  • Answers Posted: 7 July 2021 and 20 July 2021
  • Applications Due: 27 July 2021 (6pm PT / 2am WAT / 4am EAT)

Question and Answer Period: All questions related to the EOI should be submitted to with “Equity & Health 2021 Question” in the subject line. Additional questions submitted by 16 July will be de-identified and answered publicly by 20 July on the Lacuna Fund website in a document posted here.

Past Funding Opportunities

All past Funding Opportunities can be found here.

Focus Areas

The Steering Committee of Lacuna Fund: Our Voice on Data has identified the following areas as domains where a lack of labeled training data limits the potential of machine learning or presents the risk of bias or inequity.


Enabling new and more robust AI applications through remote sensing and other critical datasets.


Translation, speech recognition, and other datasets to enable the promise of digital communication for all.


Improving the robustness and availability of AI solutions in healthcare through datasets across the value chain.