Grant and public-funding collaboration page for programs, foundations, innovation funds, public funders, and ecosystem organizations interested in supporting inAi's AI-native products, Open Source tools, public AI education, Products for Agents, research, and real-world AI adoption.
inAi builds AI-native products and open technology for the intelligence era.
Some of this work is commercial. Some of it is public. Some of it is experimental. Some of it sits between product development, research, Open Source, public education, workforce change, and real-world AI adoption.
The Grants path is for organizations that fund useful work in that space.
This page is for grantmakers, foundations, innovation programs, public funding programs, AI ecosystem funds, European and French support programs, accelerators, research-funding bodies, and public-interest organizations that may want to support inAi’s work.
inAi is not looking for vague innovation theatre. We are interested in funding relationships where scope, outputs, reporting, public value, and expectations are clear.
This page is for funding organizations and programs that want to support serious AI work with public or ecosystem value.
You may also use this page if you are not a funder directly, but you know a grant, program, foundation, or public funding route that may fit inAi.
inAi is a product company, but not every valuable product-company activity is funded best by immediate commercial revenue.
Some work creates public value before it becomes a product. Some work helps an ecosystem. Some work needs careful research before it can become reliable. Some work should be available in the open. Some work helps people understand a technology that is changing faster than public understanding can follow.
Grants can help inAi move faster on work that matters beyond one customer or one narrow product.
A grant should not make inAi pretend that something is more mature than it is.
The right grant helps us develop, test, explain, publish, open, or evaluate useful work with honest maturity labels.
inAi is not a generic consultancy and not a research lab without products.
The company’s value is the connection between product work, research direction, Open Source, public explanation, and real implementation.
Grantmakers need more than excitement. They need a serious team, a coherent scope, an understandable outcome, and a public-benefit logic.
Depending on the program, inAi may be able to offer a clear AI-native product-company thesis; public pages explaining the work; concrete product categories; existing product baselines through PageMind and Emplo; public Open Source repositories where relevant; research-facing pages and public stance material; AI education and public explanation through AI for Everybody; structured reporting on what was built, tested, published, or learned; honest maturity labels; clear separation between current product, research, Open Source, experimental, pre-launch, and future-facing work; connection between product, research, education, and ecosystem work; public communication through News where appropriate; and careful handling of private data, product internals, and unsupported claims.
inAi should not promise what it cannot support.
We will not claim fake users, fake customers, fake partnerships, fake metrics, fake public launch status, or fake institutional endorsement.
A grant can be valuable without becoming exaggerated publicity.
A useful grant conversation should clarify funding amount or expected budget range; program goals; eligibility rules; geographic or legal requirements; deadlines; reporting obligations; expected outputs; public communication requirements; IP and licensing expectations; Open Source requirements; data handling requirements; consortium or partner requirements; whether the grant is non-dilutive; whether matched funding is required; what kind of work the program supports; whether public-facing deliverables are expected; and whether there are restrictions on commercial use, publication, subcontracting, or future productization.
The more precise the program is, the easier it is to evaluate fit.
A vague message such as “we fund AI innovation” is less useful than a concrete program page, deadline, budget, eligibility rule, and expected deliverables.
A strong grant fit usually supports applied AI, has clear outputs, has public or ecosystem value, fits a small AI-native product company, understands early-stage maturity, does not require fake public traction, has proportional reporting, has clear IP/licensing expectations, has realistic Open Source obligations, does not require private infrastructure or data exposure, connects naturally to an existing inAi page or product category, and can be described publicly without implying endorsement beyond what is true.
A weak grant fit usually creates more distortion than value.
Depending on the program, grant-funded work could produce product prototypes, product-category improvements, controlled pilot results, research notes, public explainers, AI for Everybody guides, diagrams and accessible visuals, Open Source repositories, Open Source documentation, technical examples, evaluation frameworks, workflow analyses, translation or accessibility improvements, public News updates, final reports for funders, lessons learned from real workflows, partner-facing or public-facing summaries, educational resources, workshops, structured sessions, and selected public artifacts that help other builders or users.
Not every grant needs every output. The output should match the scope.
A small grant may support documentation, public explanation, repository cleanup, or a focused prototype. A larger program may support pilot work, product development, research collaboration, or a broader public-education package.
If a grant is awarded, public communication should be accurate.
inAi may publish a News update, mention the grant on a relevant page, or acknowledge support in a project, page, report, repository, or public artifact if the funder allows it.
Public wording must stay precise.
Allowed wording may look like: This work is supported by [Program / Organization].
Allowed wording may look like: inAi received support from [Program / Organization] for [specific scope].
Avoid language that implies endorsement, validation, certification, safety proof, compliance proof, or product maturity beyond what the relationship supports.
Grant recognition should create trust, not fake authority.
Do not send sensitive material in an initial grant inquiry.
For first contact, send program information, scope, deadlines, and fit.
If a grant requires controlled data, pilot data, research data, or private materials, that must be handled through an appropriate agreement and route.
Grant funding and investment are different.
A grant usually supports a defined scope, public benefit, research direction, product development, education work, Open Source work, pilot, or ecosystem contribution. It may be non-dilutive and tied to deliverables or reporting.
Investment supports the company as a business and may involve equity, financing structure, investor materials, and long-term company growth.
Some public or institutional programs fund innovation. Others buy services, products, studies, or implementation work.
If the organization wants to buy or test a product, use Pilots / Corporate partners or the relevant product page.
If the organization wants public-sector collaboration, use Government / Public institutions.
If the organization wants to support a project, research direction, Open Source tool, education layer, or public-benefit work, use this Grants page.
Clear routing saves time.
Some grants support Open Source. That can fit inAi well.
However, Open Source funding must be precise.
Useful Open Source funding may support documentation, setup improvements, tests, examples, maintenance, package quality, issue handling, developer guides, public tutorials, accessibility, tool reliability, and public explanation of how a tool should be used.
Open Source grant conversations should respect project maturity. Some repositories are active. Some are experimental. Some are reference utilities. Some are legacy or historical. A grant should not force a legacy prototype to be described as production infrastructure.
Some grants support research. That can fit if the research is connected to inAi’s public directions.
Relevant research areas include Limits of Intelligence, Agentic Decision Systems, AI for Knowledge Creation, AI and Business Operations, AGI as a System, Products for Agents, AI-native systems, tool use, memory, coordination, evaluation, and real-world workflows.
Research grant work should be clear about output type.
Possible outputs may include research note, public essay, evaluation method, experiment report, technical prototype, Open Source artifact, public explainer, research collaboration, workshop, seminar, or product-facing lessons.
AI for Everybody is a natural fit for public-interest funding.
It can support simple explanations of AI, public myths and fears, AI and work, AI and education, agents, AGI and ASI concepts, AI risks and guardrails, accessible diagrams, plain-language guides, French and English public materials, content for nontechnical readers, and materials for students, job seekers, small businesses, or public institutions.
This kind of grant should not produce fake authority or generic “AI awareness” content. The goal should be honest understanding.
Some grants are designed to test technology in real environments. That may fit inAi when the pilot is scoped and honest.
Possible pilot-related grant areas include product-data workflows, PageMind retail/catalog use cases, SME AI adoption, business operations, agent-facing software tests, public-sector workflow exploration, job-seeker support or employability workflows, Open Source tools in practical use, and education or public-explanation delivery.
A pilot grant should define the workflow, participants, expected output, data boundary, timeline, what will be public, what will remain private, how success will be evaluated, and whether the result is a public report, internal learning, product improvement, repository update, or broader collaboration.
A useful grant message should be specific.
Include who you are; grant or program name; funding type; budget range; deadline and timeline; eligibility rules; expected scope; expected outputs; IP, Open Source, and publication requirements; reporting requirements; why inAi may fit; and contact details.
Do not ask inAi to make unsupported public claims in exchange for funding.
Do not send an initial grant message that only says “Do you want funding?”, “We support AI startups. Send us your deck.”, “We have a grant, but the details are not public.”, or “Can you make something AI for our program?”. Those messages are too vague to route well.
Do not send confidential program details if you are not allowed to share them.
Do not send sensitive data, credentials, private documents, customer data, candidate data, supplier data, or security-sensitive information through a general inquiry.
Use Contact when available and choose the closest grants or funding route.
Suggested contact route: Contact -> Grants / funding.
If email is needed, use partnerships@inai.world.
Suggested subject line: Grant collaboration — [Program / Organization] — [Scope].
For research-only collaboration, use research@inai.world with subject line Research funding collaboration — [Topic] — [Organization].
For investment, do not use this route. Use Investors.
