Try
Put your current understanding into words. A first attempt makes room for the ideas you already have.
Meet Zenito
A thinking partner.
Room for you.
We're exploring personal AI that knows when a hint is more useful than a finished answer. One that helps you build understanding you can carry away.
In developmentFollow the build
Understanding takes an active mind
The answer is a start.
Make the reasoning yours.
Ever read a perfect explanation, then struggled to explain it yourself? We're exploring a different rhythm: try, get a hint, understand, and recall.
zenitoConcept demo · scriptedA moment of reasoning · binary search
Why does binary search need a sorted list?
Start with your intuition. What lets us discard half the list?
Local example. No AI service. No saved answers.Skip example
The proposed experience
Assistance with a little breathing room.
Hint
Get a useful nudge toward the next step. In our example, sorting tells you which half of a list cannot contain your target.
Explain
Connect the hint to the underlying reason. In binary search, ordering lets us safely eliminate half of the remaining candidates.
Recall
Use that reasoning again without the explanation in front of you. If the target is smaller than the middle, discard the middle and the right half.
What we're exploring
Adapt the support.
Keep the agency.
A beginner meeting a new concept and an experienced developer checking a detail need different kinds of help. We're investigating how an assistant could respond to that context without assuming it knows your mental state.
Read the cognitive-engine notesProduct status
An idea in active development.
Our research covers retrieval, preference alignment, model fundamentals, and adaptive guidance. Integration, evaluation, and device requirements remain open work.
Public releaseNot announced
Supported devicesBeing explored
Learning outcomesTo be evaluated
This site's demoScripted concept
Private by intention
Your context.
Your machine.
Your mind.
Personal assistance needs personal context. We believe that context should be yours to control.
We're designing Zenito around on-device processing: bringing the model closer to you, instead of sending your life to a distant server.
An architectural goal. Hardware requirements and the final data model are still being explored.
Your device
Your questionsYour notesYour goals
ZenitoLocal intelligence
Guidance, shaped around you
Intended on-device boundary
A little more context
Good questions.
Straight answers.
What we're building,
and what we're still figuring out.
What is Zenito?
Zenito is a personal AI being developed by Xlon Labs. The goal is to help you practise reasoning, recall, and problem-solving, with guidance that leaves room for your own effort.
Who is it being designed for?
Our starting point is developers, technical learners, and curious professionals who want to understand what they learn and explain it independently. These are intended use cases; we are still exploring how best to serve them.
Can I use Zenito today?
Zenito is in development. A public release date and download have not been announced. The interactive example on this site shows a proposed learning flow, not the released product.
Is the interactive demo real AI?
It is a scripted concept demo. Its questions, hints, and answers are written in advance. Your choices stay in this page’s memory and reset when you reload; they are not sent to an AI service.
What does “on-device” mean?
Our design goal is for personal context and model inference to stay on your device. That is a direction for the product, not a claim that every part is implemented. This website still uses normal web hosting, and research notes may describe external APIs.
What hardware will I need?
Supported operating systems, memory requirements, and model configurations have not been announced. Local inference efficiency is one of the questions guiding our research.
How is this approach meant to help me learn?
The proposed flow invites an attempt before assistance, offers a targeted hint, makes the reasoning explicit, and gives you a chance to recall it. It is a design approach we intend to evaluate, not a promise of measured learning gains.
How can I follow progress?
Read the research notes and check the Follow the Build page. We will share confirmed access details there when they are available.
The next chapter
Raise your ceiling.
Follow the work toward AI that leaves you more capable.