PARTNERS / PILOTS
Pilots / Corporate partners
Selected collaborations with companies whose operational or product problems may align with what inAi is building.
inAi develops AI-native products for a world in which intelligence becomes part of software and work. Some product questions are best answered in operational context: with existing systems, imperfect information, actual users, review requirements, and decisions that matter.
We are open to selected conversations where a company can bring that context and there is a credible reason to explore the fit together. PageMind is the clearest current product-pilot route. Other collaborations are considered selectively when the problem closely matches work already in development.
A pilot starts with a problem worth testing
At inAi, a pilot is a focused collaboration around a real workflow or product problem. It is intended to answer a practical question: can an inAi product, or a product direction we are already developing, create enough value in this context to justify a next step? The strongest starting point is a specific problem rather than a general wish to “use AI.”
You do not need to arrive with a finished specification or know which inAi category is relevant. A clear account of the problem, how it is handled today, who it affects, and what you would like to understand or improve is enough to begin.
Pilots are shaped around the situation rather than sold as a standard package. Where there is a credible fit, both sides agree what will be explored, what each side will contribute, what a useful result would mean, and which practical, commercial, data, or confidentiality conditions need to be settled before work begins.
If the primary need is a system designed specifically around your organization, rather than an inAi product or product direction, the better route may be AI Services.
Where a collaboration may fit
PageMind
Current product · Private Beta / selected pilot conversations
PageMind is the clearest current product-pilot route at inAi. It is built for retail, e-commerce, catalog, and product-data teams working with fragmented supplier information, product documents, spreadsheets, images, multilingual content, and review-heavy workflows.
A PageMind conversation may be relevant when the goal is to turn inconsistent product inputs into structured, reviewable information that can move into real catalog or product-content work.
Selected product collaboration
Considered case by case
We also consider company problems that closely match business-product or agent-facing work already in development. These conversations begin with the company’s problem, not with a promise that a standard product or pilot already exists.
A useful proposal may involve an operational information bottleneck, an AI-native product workflow, or software that needs to become more usable by AI agents. We continue only where the problem, the current state of our work, and the potential value align.
What makes a useful starting point
The strongest proposals are not necessarily the most polished. They are the ones grounded in a real situation.
A concrete problem
A workflow, product, information flow, or software surface that is difficult, fragmented, slow, inconsistent, or ready to be redesigned.
An understandable current process
Enough context to explain how the work happens today, who is involved, what inputs exist, and where the friction appears.
People close to the work
An internal owner and access to the people who understand the workflow well enough to explain it and judge the result.
A way to judge usefulness
A practical basis for deciding whether the product, workflow, or technical direction improved anything that matters.
Mutual value
A reason the collaboration could help the company make a better product or operational decision while giving inAi useful product understanding from real conditions.
The process does not need to be clean, and the information does not need to be perfect. It only needs to be understandable enough for both sides to identify what is worth testing.
What each side brings
What inAi brings
inAi brings AI-native product thinking, the relevant product work, and a disciplined way to turn an open question into something testable. We are direct about what is current, what is still developing, and what can reasonably be assessed. Where there is a fit, we help define the smallest collaboration that could produce a useful answer.
A useful pilot depends on both sides contributing something the other does not have.
What the corporate partner brings
The partner brings the workflow, domain context, representative material that can be prepared safely, people who understand the work, and an honest way to judge whether the result matters. The strongest partners also have someone able to own the conversation and make the next decision.
How the conversation may proceed
1. Share the problem
Send a short description of the workflow or product problem, how it works today, who is involved, and what you want to understand or improve. Do not attach sensitive material.
2. Review the fit
inAi considers whether the problem aligns with PageMind, another product direction, AI Services, or a different collaboration path, and whether the timing and maturity make a focused next step realistic.
3. Define the collaboration
Where there is a reason to continue, both sides define the scope, responsibilities, representative inputs, expected learning or result, timing, and any practical, commercial, data, or confidentiality conditions that matter.
4. Learn and decide
The work should lead to a clearer decision. That may be to continue, adjust the direction, move to another route, revisit later, or stop. A pilot is useful when it reduces uncertainty, not only when it leads to deployment.
Clear about fit, maturity, and privacy
You can expect a direct assessment of fit. We distinguish current products from work that is still developing, and we will recommend another route when it is more appropriate.
Not every inquiry becomes a pilot, and not every pilot needs to become a deployment. A conversation or pilot is also not automatically public. We do not identify organizations or describe the work publicly without agreement.
What to send
You do not need a completed specification. A useful first message includes:
your organization and your role;
the problem or workflow you want to discuss;
how the work is handled today and where the main friction appears;
who uses, owns, or evaluates the workflow;
what you would like to understand, improve, or test;
why inAi may be relevant, and any timing that genuinely matters.
Do not attach confidential, personal, proprietary, or security-sensitive material to an initial inquiry. Describe the type of information instead. If both sides decide to continue, any confidentiality, data, access, legal, or commercial requirements are agreed before sensitive work begins.
Start a pilot conversation
Tell us what is happening today, where the problem appears, and what you believe could become better. We will assess whether PageMind, another product direction, AI Services, or a different inAi route is the right place to continue.
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