GitLab Foundation

Quick Stats

Annual Giving: $14,106,133 (2025)
Success Rate: ~4.2% (27 grants from 650+ applications over first two years of AI Fund)
Decision Time: Varies by program; two-stage application process
Grant Range: $50,000 - $2,900,000
Average Grant: $295,900
Geographic Focus: United States (primary), Colombia, Kenya (international expansion)

Contact Details

Website: https://www.gitlabfoundation.org

Public Handbook: gitlabfoundation.notion.site

Social Media: LinkedIn and Instagram (@gitlab_foundation)

Overview

The GitLab Foundation (EIN: 87-4241796) is an independent global private foundation established in 2021 and based in San Francisco, California. Operating as a fully remote organization, the foundation holds assets totaling $23,027,115 with annual giving of $14,106,133 (2025). The foundation's mission is to help people grow their lifetime earnings through education, training, access to employment, and systems change on a global scale. With an ambitious "North Star 100X goal," the foundation targets generating over $100 in lifetime earnings gains per dollar spent. Since inception, they have awarded over $5.5 million to more than 200 grantees through their AI for Economic Opportunity initiatives, focusing on populations earning below a living wage. In 2025, the foundation launched two new strategic initiatives: an advisory services practice supporting peer foundations in impact modeling, and a donor engagement strategy to attract additional values-aligned capital.

Funding Priorities

Grant Programs

AI for Economic Opportunity Fund

Demonstration Phase: Up to $250,000 seed funding
Scaling Phase (with Ballmer Group): $500,000 - $1,500,000 annually (1-2 year grants)
Partners: Ballmer Group and OpenAI
Total fund value: Over $5.5 million awarded to 27 grantees
Application: Two-stage process (concept notes, then full applications for finalists)
Deadline: Rolling basis with annual calls (recent deadline: October 31, 2025)

Powering Economic Opportunity Fund

Joint partnership with Families & Workers Fund
Total: $16 million over two years
Recent round: $4 million to 10 projects
Focus: Propelling low-wage workers into high-growth careers in renewable energy, infrastructure modernization, and advanced manufacturing

Learning for Action Fund

Grant size: Approximately $50,000 per grant
Recent round: $600,000 across 12 grantees
Focus: Impact measurement and evaluation capacity building

Priority Areas

Economic Mobility Through Technology

AI-driven solutions for workforce development
Tech training and apprenticeships for underrepresented populations
Digital platforms improving job matching and career guidance

Workforce Development

Job training and placement programs with measurable income outcomes
Registered apprenticeships in high-growth sectors
Skills development for populations earning below living wage

Green Jobs and Climate Careers

Clean energy career pathways
Climate-tech apprenticeships
Infrastructure modernization workforce training

Systems Change

Addressing human capital supply/demand mismatches
Credential quality assessment and adoption
Benefit delivery system improvements (e.g., SNAP enrollment)

Financial Inclusion

Microenterprise support for women and immigrants
Credit access for underserved populations
Financial literacy and stability programs

Support for Specific Populations

Immigrants and refugees
Formerly incarcerated individuals
People with disabilities
Trafficking survivors
Women in male-dominated industries
Smallholder farmers in developing countries

What They Don't Fund

Political lobbying, propaganda, or campaign activities
Distributions that benefit private individuals rather than charitable purposes
For AI for Economic Opportunity Fund specifically:
- Incremental improvements without AI integration
- Pilot concepts that don't demonstrate transformative use of AI
- Non-US-based organizations (though programs may operate internationally)

Governance and Leadership

Board of Directors

Caroline Whistler (Board Chair)

Co-founder and CEO of Third Sector
Expertise in advising government agencies on reshaping policies, systems, and services for better outcomes
Brings deep grasp of systems-level change and cross-sector partnerships

Benjamin Alex

Deputy Director of Finance at the Gates Foundation
Expertise in philanthropic finance, strategic grantmaking, and measuring social impact
Background in evaluating catalytic investments and optimizing resource allocation

James Shen

GitLab's interim Chief Financial Officer
Expertise in scaling financial operations and driving strategic growth
Previous roles at Meta and DocuSign
Guides Foundation's ROI-focused grantmaking model toward $25 billion lifetime earnings goal

Leadership Team

Eleanora "Ellie" Bertani (President & CEO)

Leads the Foundation's mission to improve lifetime earnings and economic mobility worldwide
Emphasized: "Access to education and training helps workers build new skills and advance in their professional lives, driving income growth and economic mobility"
On collaboration: "One of the most important things is collaboration across the sectors. I really think that in this space that's one of the most promising ways to make an impact in people's lives"
On AI: "We invest in what we hope AI will be — a driver of possibilities for humanity and public benefit, rather than just profit"

Roger Perez (Program Officer)

Provides guidance on building compelling applications

Governance Structure

Incorporated in California on December 2, 2021 as a nonprofit public benefit corporation
Directors and committee members serve without compensation but may be reimbursed for reasonable expenses
President manages operations subject to Board oversight

Application Process & Timeline

How to Apply

AI for Economic Opportunity Fund:

Submit concept note through online application form by deadline
Applicants may submit up to three concepts
Finalists selected from concept note pool are invited to submit full applications
Recent application deadline: October 31, 2025

Other Programs: The Foundation generally does not accept unsolicited applications outside of its structured programs. Grants are made through announced funding opportunities and partnerships.

Eligibility Requirements

For AI for Economic Opportunity Fund:

Must be US-based nonprofit organization (501c3)
Programs may operate internationally
Partnerships between nonprofits and for-profits (startups, consultants, tech experts) strongly encouraged
For-profit social enterprises considered case-by-case with fiscal sponsor or nonprofit partner
Must demonstrate transformative use of AI (not incremental improvements)
Must focus on improving economic mobility for low-income populations

Decision Timeline

Timeline varies by program. The AI for Economic Opportunity Fund uses a two-stage process:

Concept note review and finalist selection
Full application review for invited finalists

Specific timeframes from submission to decision are not publicly disclosed but successful applicants receive funding along with exclusive access to AI technical support, peer learning opportunities, and potential scaling opportunities.

Success Rates

AI for Economic Opportunity Fund: Approximately 4.2% success rate

Reviewed more than 650 applications over first two years
Awarded 27 grants

Overall Portfolio:

62 awards made in 2025
30 awards made in 2024
Average grant: $295,900

Grant Sizing Strategy

According to CEO Ellie Bertani: "The foundation scales the size of grants based on risk, so if they feel like it's a newer team, if they like the idea, they'll still fund it, they'll just give them a smaller amount, and then if they do well, they'll give them more."

Reapplication Policy

Specific reapplication policies for unsuccessful applicants are not publicly documented. Applicants should refer to program-specific FAQs or contact the Foundation directly for guidance.

Application Success Factors

Demonstrate Measurable Impact on Lifetime Earnings The Foundation's North Star metric is $100+ in lifetime earnings gains per dollar invested. Successful applications show clear pathways to measurable income increases for beneficiaries. For example:

mRelief's SNAP Assistant demonstrated 311x ROI with $1,368 annual income increases per person for 30,740 individuals
Digital Green's Farmer.Chat achieved 549x ROI with 8% income increases for 155,505 farmers
FreeWorld's CDL program showed 191x ROI with $45,000 annual income increases for 360 individuals

Focus on Populations Earning Below Living Wage Successful grantees specifically target underserved populations: immigrants, refugees, formerly incarcerated individuals, people with disabilities, women in male-dominated fields, and workers in the informal economy.

Leverage AI for Transformation (for AI Fund) Applications must demonstrate transformative—not incremental—use of AI. Examples from funded projects:

CareerVillage's AI career coach scaling to 10 million learners
Immigration Policy Lab's GeoMatch machine learning tool improving refugee employment matching by 30-50%
Per Scholas' system screening 10,000 learners for public benefit eligibility

Build Cross-Sector Partnerships CEO Ellie Bertani emphasizes: "Collaboration across the sectors...is one of the most promising ways to make an impact." Successful applicants often partner with:

Technology companies and startups
Employers committed to inclusive hiring (Microsoft, Visa, Salesforce, Walmart)
Government agencies
Academic institutions

Align with Foundation Values The Foundation operates on values of collaboration, results, efficiency, diversity, iteration, and transparency. Applications should demonstrate alignment with these principles.

Show Scalability Potential The Foundation invests in "catalytic" approaches that expand institutional reach, reduce barriers to accessing services, and improve cost efficiency. Successful projects demonstrate potential to scale beyond initial implementation.

Address Systems-Level Change Beyond direct service delivery, the Foundation values investments that address structural barriers and human capital supply/demand mismatches, such as:

Burning Glass Institute's $2.9M grant for credential quality assessment framework
RIPL's work bridging nonprofits with state administrative data analytics

Risk-Adjusted Approach The Foundation will fund newer teams with smaller initial grants, increasing funding based on demonstrated results. This suggests applications from emerging organizations should focus on proof of concept and clear success metrics.

Key Takeaways for Grant Writers

Lead with lifetime earnings impact: Quantify expected income gains per dollar invested—the Foundation's North Star is 100x ROI
Highly competitive process: With ~4% success rate for AI Fund, applications must be exceptionally strong and data-driven
AI must be transformative: For AI Fund applications, incremental improvements won't cut it—demonstrate how AI fundamentally changes reach, efficiency, or outcomes
Geographic focus matters: While US-based organizations are required, the Foundation has identified Colombia and Kenya as international priority countries
Partnership strengthens applications: Cross-sector collaborations (nonprofit + for-profit, academic + employer) are strongly encouraged
Prepare for iterative funding: Smaller initial grants can grow with demonstrated success—focus on proving your model
Transparency and measurement are essential: The Foundation maintains a public impact dashboard and expects rigorous outcomes tracking from grantees

References

All information accessed December 2024.