About Ylan

YlanAI is a structured analysis assistant built for real-world decision scenarios.
It is not a guaranteed-outcome tool. It is a support method that helps you see the structure of a problem, identify risks, and arrange the pace of action.

Our Positioning

YlanAI focuses on decision quality instead of manufacturing certainty.
Its core goal is to turn complex information into analysis that is readable, comparable, and actionable.

We care most about three things:

• clarify the problem before discussing direction
• identify the risk boundaries before arranging pace
• give actionable suggestions before running review and calibration

How The Analysis Works

Under the same input conditions, the system produces structured output through a consistent logic. Common parts include:

1. Core judgment: the most important opportunities and risks in the current problem
2. Structural reading: stable factors, fluctuating factors, and trigger conditions
3. Scenario suggestions: strategic reminders across career, relationships, finances, and similar themes
4. Action list: priorities, execution order, and review checkpoints

Note: these modules are not a fixed template. They change with the version, problem type, and completeness of input.

What Kinds Of Problems Fit

YlanAI works best for issues that require tradeoffs, prioritization, and pacing, such as:

• career path choices and stage strategy adjustments
• conflict recognition and repair priority in relationship communication
• financial pacing and risk-boundary management
• action order and tradeoffs around key turning points

What Should Not Rely Only On This Service

The following should not use this service output as the final conclusion:

• medical judgments
• legal or compliance conclusions
• major financial commitments or investment decisions

For these scenarios, rely on real evidence and consult qualified professionals.

Input Requirements And Quality

Input quality directly affects output usefulness. It helps to provide at least:

• one clear core question
• key timelines and stage changes
• current real-world constraints and resource boundaries
• methods already tried and the risks you worry about most

If part of the background information is still uncertain, mark what is confirmed and what is pending first, then keep refining the input against real feedback.

What We Mean By “Accuracy”

When YlanAI talks about “accuracy,” it mainly means:

• logical consistency: the same input can be checked again
• clear expression: the conclusion has a basis and can be compared
• usable suggestions: the output can be turned into real action

This does not mean a guaranteed outcome or a deterministic promise about the future.

Recommended Way To Use It

To get more useful results, use it in this order:

1. Read the core judgment first and confirm the main axis of the problem.
2. Read the risk reminders and confirm the boundary conditions.
3. Read the action suggestions and turn them into executable steps.
4. Keep reviewing and revising based on real feedback.

Analysis Premises And Limits

The output is generated automatically by AI and may contain errors, omissions, or mismatches with an individual situation.
The output is provided for learning, research, communication, and entertainment reference, and it does not constitute medical, legal, investment, or other professional advice.

Final decisions should be made independently by the user based on real context.

Notes For Minors

Minors are advised to use the service with guidance from a guardian.
The output should not be the sole basis for major decisions such as schooling or career direction.

Privacy And Data

We take privacy seriously. The current policy is:

• we do not use birth information, question content, or chat records for model training
• we do not sell or share them with third parties
• we do not store personal inputs or chat content for the long term by default
• users can delete chat records or clear history through in-product features

If required by law or clearly authorized by the user, we will process the data under the applicable rules.

Ongoing Updates

We will keep improving the way the analysis is expressed, structured, and guided as the product evolves.
If any rules or functions change, the current page and the related rules pages will prevail.