the product
Studinari and Ruminari look nothing alike and solve different problems. What they have in common is everything you cannot see: Alunori is the AI UX platform they both stand on, and neither of them started at a blank page.
shared underneath One layer — context held, carried between sessions, and answered to the person actually asking.
the platform
Alunori is a platform in the only sense that matters: the hard part is built once and every product inherits it. A new Nari project arrives already able to hold a person's situation, carry it across sessions, and answer them rather than a generic user. What the project adds on top is its surface — and that is the only part anyone has to invent.
Memory of the person, continuity between sessions, and a sense of how this particular one should be answered. It is the same thinking under a study workspace and under a conversation tool, because the problem underneath is the same problem.
The domain, the vocabulary, the screens, the job. A student's week and a long chat thread have nothing in common on screen, and nothing here pretends otherwise. A family is an approach, not a template.
That split is why two very different products still read as one company, and why the third will take a fraction of the time the first one did. The naming says it out loud: the prefix is the surface, and the ending is the layer.
product one
A study workspace where plans, practice, and reflection live in one system instead of five apps, run by an AI team that already knows where the student is. It was the first project to earn the Nari ending, and it is open now.
Home, planner, AI, profile. Everything the product does lives inside one of them, and each one is complete on its own.
A Lead Consultant holds the goal and hands work to a tutor, a coach, a researcher. They report to it, not to you.
Weeks of plans, gaps, and pace are what make the advice specific. Swap the model underneath and that is still what does the work.
product two
Where Studinari applies the layer to a student's term, Ruminari applies it to a single conversation — the place almost everyone using AI seriously loses time. It is the platform sold as itself, and it is still being built.
Your intent goes in; a clearer, better-specified version comes out, so the first answer is closer to the one you were after.
As a session runs long, what has fallen out of context is noticed and restored — without stopping to re-explain the setup again.
Both are work that happens around the model, which is why a better model has never fixed either one.
what comes next
Studying and prompting were the first two places the experience broke down badly enough to build for. They are not the last — the same layer points at how people keep what they learn, how they decide, and how they pick things back up after a week away.
A project earns the Nari ending only once losing it would actually cost you something. That is the bar, and it is the reason there are two names here and not ten.