Mercor AI Research Fund Grants

About Mercor

Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents.

Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.

Mercor AI Research Fund Grants $5M

One of the biggest challenges facing the industry today is determining whether frontier AI is capable enough to deliver value in real-world settings. A model can perform well on benchmarks and still struggle in production. That’s why investing in research, realistic evaluations, and robust verification is critical.

Mercor is committing $5 million to fund AI research. Award size and mix depend on the project. The grant supports:

• The time of experts from Mercor's platform

• Researcher hours

• API costs

• Stipends for event and conference attendance

This is separate from the Mercor Research Fellowship, which funds individual experts (apply HERE) and our $5m of safety funding awards (apply HERE).

What we're looking for

• Real-world evaluations: measuring whether benchmark performance translates into reliable performance on realistic tasks and workflows

• Environments: building high-fidelity, interactive environments that capture the complexity of real-world work

• Long-horizon tasks: evaluating and improving models’ ability to plan, execute, and adapt across extended workflows

• Agentic capabilities: tool use, coordination, memory, and autonomous execution

• Reasoning and problem-solving: improving performance on complex, ambiguous, or underspecified tasks

• Post-training: developing better data, rewards, and training methods to improve model capabilities

• Evaluation methodology: creating more robust measures of capability, reliability, and real-world utility

Why us

• Funding for researcher time, API costs, and event attendance

• Where useful to the work: access to Mercor's expert network for human grading and annotation: lawyers, accountants, engineers, scientists, clinicians

• Access to Mercor's internal evaluation infrastructure, subject to review

• Introductions to Mercor's network of researchers across frontier labs and academia

Who should apply

• Researchers at universities and non-profit research organizations, as well as public benefit corporations and small startups that do not sell AI training data. Awards are made to the researcher’s institution.

• People with a specific, well-scoped question: the grant is built around your proposal, not a generic research rotation

• Applicants based in the United States or the United Kingdom

• Bonus: researchers with experience with agentic evaluation, RL environments, and post-training.

We expect grantees to publish - such as a paper, an open dataset, a public methodology, or a tool the field can use, released under an open license that permits commercial use.

Award terms

Selected grantees will sign Mercor’s research award agreement. Key terms include:

• Grantees keep ownership of their work and grant Mercor a non-exclusive license to use it, including commercially.

• Mercor may identify grantees and their institutions as award recipients, including by name and logo. Grantees may use Mercor’s logo with Mercor’s approval.

• For benchmark and evaluation projects, Mercor receives early access to the benchmark before public release and the exclusive right to build and host a private held-out test set, at Mercor’s cost.

• Grantees agree not to work with specified Mercor competitors on substantially similar benchmarks or evaluations during the award and for 12 months afterward.

• Grantees are free to publish their findings. Mercor reviews drafts in advance only to remove its confidential information.

• Awards are subject to tax documentation, sanctions screening, and periodic progress reports.

How to apply

Submit an Expression of Interest. We expect to see a one- or two-page document. It should contain at least a section on your team, background, and research accomplishments; a section on your proposed research project; and a section on the outputs and impact of the project, with directionally correct timelines and resource requirements. Please do not include confidential or proprietary information in your Expression of Interest. Submitting an Expression of Interest does not obligate Mercor to make an award.