PARTNERS / PUBLIC SYSTEMS
Government and public institutions
Public institutions shape how new technology reaches public services, workers, learners, companies, industries, and the wider public. inAi is open to serious institutional conversations where our AI-native products, AI Services, Research, public explanation, or Open Source work can contribute to a defined objective.
Bring us a mandate, problem, programme, or collaboration idea. We will determine whether there is a credible route through current work, a tailored implementation, a scoped pilot, Research, education, Open Source, or a funded initiative—and be clear when there is not.
Start with the objective
Public institutions do not need AI for its own sake. They may need a service to become easier to use, an internal workflow to become more effective, a body of information to become more accessible, a public programme to support adoption, a research question to be evaluated, or a complex technology to be explained clearly.
We begin with that objective rather than a predetermined feature. We look at who is affected, how the work happens now, which constraints matter, and what a useful result would look like. The answer may be a current product, a tailored system, a bounded pilot, a research or evaluation project, a public resource, an Open Source contribution—or a conclusion that AI is not the right first step.
Where collaboration may fit
AI Services and implementation
For institutions with a defined information, document, knowledge, software, or workflow problem. Work may begin with discovery and feasibility, then move into a prototype, integration, tailored application, or another scoped implementation where there is a credible fit.
Products and scoped pilots
Where an inAi product or product direction matches a real need, we may explore controlled access, structured feedback, or a bounded pilot. We clarify the product’s current stage, what can actually be tested, and what decision the pilot is intended to support before proposing a format.
AI literacy and public understanding
For institutions helping people understand AI, agents, work, risks, opportunities, and the systems around them. Collaboration may involve guides, workshops, visual explanations, public resources, or materials developed for a clearly defined audience.
Research and evaluation
For public labs, programmes, research teams, and institutions working on agentic systems, knowledge creation, AI in operations, the limits of intelligence, or the evaluation of AI-native workflows. Possible outputs may include research notes, methods, workshops, evaluations, or prototypes.
Open Source and public technology
For selected technical work that benefits from openness: reusable tools, documentation, reference implementations, developer resources, or contributions to public digital ecosystems. Each project retains its own maturity, licence, and maintenance context, so openness is not confused with maturity or operational support.
Workforce, industry, and innovation programmes
For programmes involving employability, skills, SMEs, sector adoption, entrepreneurship, or regional innovation. inAi may contribute products, technical work, public explanation, Research, or Open Source where the programme has a defined objective, a credible role for inAi, and an expected output. Funding-led work may take the form of a grant, consortium, or defined programme work package.
The right format depends on maturity
The parts of inAi that are relevant to institutions do not all have the same maturity or availability. We distinguish work that can be scoped through AI Services from controlled product access, a bounded pilot, a public Open Source project, a Research direction, an educational resource, and a product direction that still requires development.
Before proposing a collaboration, we clarify what already exists, what would need to be built, what can be tested, and what remains exploratory. This allows us to discuss ambitious institutional work without presenting every part of inAi as equally mature or ready for the same kind of engagement.
How an institutional conversation becomes real work
1. Understand the objective
We review the institution’s mandate, the intended users or beneficiaries, the current situation, the desired outcome, and the principal constraints already known.
2. Choose the right route
We determine whether the strongest connection is to an existing product, AI Services, a scoped pilot, Research, AI for Everybody, Open Source, a grant, a public programme, or a consortium.
3. Define the engagement
Where there is a credible fit, the scope, responsibilities, data access, technical approach, review model, budget, timing, ownership, and relevant legal or procurement conditions are defined for that specific engagement.
4. Agree the first output
The first output may be a feasibility brief, prototype, pilot, tailored system, research or evaluation result, public resource, reusable Open Source resource, or defined programme work package.
An initial conversation is a fit review. It is not a commitment to deliver, fund, procure, or publicly announce a partnership.
What makes a collaboration substantive
The institution brings
The institution brings its mandate, domain and operational context, a responsible project owner, access to relevant expertise and environments where appropriate, a governance and approval path, and the ability to evaluate the result or make the next decision.
A strong starting point has a clear public or institutional objective, an identifiable audience or beneficiary, a responsible institutional owner, a plausible connection to inAi’s work, and an expected output or decision. The strongest institutional value is usually not visibility. It is a credible route from a real need to useful work.
inAi brings
inAi brings AI-native product and system thinking, technical implementation through AI Services where relevant, Research and evaluation, public explanation, selected Open Source work where openness creates value, and clear communication about maturity, scope, and boundaries.
Conditions are defined for the actual engagement
Public institutions differ in mandate, procurement, data sensitivity, infrastructure, accessibility, accountability, and legal requirements. We therefore do not apply one standard model to every collaboration.
Where a conversation develops into operational work, the relevant technical, data, security, legal, procurement, ownership, evaluation, handover, and public communication conditions are established during scoping and reflected in the appropriate documents before sensitive access or delivery begins.
Consequential, regulated, or sensitive public uses require formal review and may fall outside the scope of an initial collaboration. Any public description of a discussion, programme, grant, pilot, or partnership should reflect its actual status and be agreed where necessary.
What to send
A useful first message does not need to be a finished specification. It should provide enough context for us to understand the objective and route the conversation properly.
Please include:
the institution, department, or programme, and your role;
the public or institutional objective;
the intended users or beneficiaries;
the type of collaboration being considered;
a relevant public call, programme, procurement notice, or other reference link, if applicable;
important timing and any major known constraints that can be disclosed safely;
the preferred next step.
Please do not include confidential, personal, classified, security-sensitive, or production data, credentials, or system-access details in the first message.
Use the route that matches the main purpose
Grants
Use the Grants route when the primary purpose is a funding programme, grant application, or defined publicly funded work package.
Academia and Research
Use Academia / Research when the relationship is organized primarily around a research question, method, evidence, or research output.
Pilots and corporate partners
Use Pilots / Corporate partners when the primary goal is to validate a product or repeatable product direction inside a real organizational workflow.
AI Services
Use AI Services when the need is already a tailored technical system, application, integration, or implementation around the institution’s own workflows and constraints.
Start an institutional conversation
Share enough context for us to understand the objective, identify the relevant part of inAi, and determine whether there is a credible next step.
Use Contact and choose Government / Public institutions, or email partnerships@inai.world.