入力したデータはどのように保護されますか。

保有資産や取引履歴などの入力データは、通信時および保存時に暗号化されます。アクセス権限は利用者本人のアカウントに限定され、第三者への提供は行いません。

AIの予測はどの程度正確ですか。

予測モデルはヒストリカルデータに基づく検証を行っていますが、将来の市場動向を保証するものではありません。信頼スコアは予測の確からしさを示す参考指標であり、最終判断は利用者自身が行う前提で設計されています。

料金体系はどのようになっていますか。

基本機能は無料で分析を開始でき、より詳細な配分提案やレポート機能は有料プランで提供します。契約期間の縛りはなく、必要に応じてプランを変更できます。

Image of using AI APP 267 data analysis platform

Centrally manage multiple revenue sources with highly accurate data analysis.

AI APP 267 continuously analyzes data on owned assets and sideline earnings and presents indicators that serve as the basis for investment decisions. It learns your risk tolerance and automatically adjusts recommended allocations in response to market fluctuations.

Start your analysis for free

Real-time indicator preview

0.82 trust score

14.3% volatility index

6 assets Class to be distributed

Issue recognition

The more people work on side jobs and investments at the same time, the more time they spend checking data.

When managing multiple sources of income in between your day jobs, you have limited time to manually reconcile market information and your own asset allocation. In reality, it would be difficult to check price fluctuations, tally profits and losses, and make rebalancing decisions every day.

In periods of high market volatility, delays in decision making directly lead to lost opportunities and excess risk. AI APP 267 automates this confirmation process and extracts and presents only the information necessary for decision-making.

2.4 hours A guide to the average amount of time an individual investor spends checking market data per week

±18% Fluctuation range of high and low prices of major indexes in the past year

3 or more Approximate number of revenue sources that users with side job income can simultaneously manage

72% Approximate percentage of users who report a decrease in update frequency during manual management

core engine

Adaptive Risk Learning automatically recalibrates as your goals and risk tolerance change.

Get input data

Get your holdings, sideline earnings, and trading history over a secure connection.

Estimation of risk profile

Quantify tolerance based on past decision-making patterns and goal settings.

Recalculate allocation

Detect changes in market conditions and update recommended allocations with Predictive Analytics.

automatic relearning

Follow target changes

When income goals or spending plans change, model parameters are updated without manual configuration.
Risk Mitigation

Controlling overallocation

If concentration in a single asset class is detected, diversification candidates are presented to reduce excess risk.
explainability

Presentation of basis for judgment

The indicators and calculation conditions that form the background of recommendations are displayed in a format that users can confirm.

dashboard

While keeping the information density high, it is organized in the order in which it should be checked.

The screen has a large number of items, but by fixing high-priority indicators at the top and placing detailed data at the bottom, we have created a structure that allows you to quickly get to the information you need.

Portfolio overview — updated today at 10:42 Update interval: 15 minutes

trust score 0.78

volatility index 16.2%

Recommended allocation change 3 items

Total side job income +4.1%

Confidence Score

This is an indicator of how well the latest model predictions are consistent with past validation data. A higher number means a better fit of the model to the current market environment.

Volatility Index

It is a numerical representation of the range of price fluctuations of a group of target assets. Understand the magnitude of short-term price movements and use this as a basis for making decisions on allocation adjustments.

Scalable Recommendations

Recalculate recommendations using the same logic as asset size and revenue sources increase. No manual threshold resetting is required.

Methodological transparency

Recommendations are based on verifiable computational procedures rather than "learned rules of thumb."

Data acquisition

We collect input data such as account information, transaction history, and side job income, detect missing values and abnormal values, and then standardize them.

pattern recognition

We use mathematical models to extract the correlation between price fluctuations and profit structure. The basis for judgment has been verified in advance through historical backtesting.

Individual optimization

It incorporates the user's target period, acceptable risk, and existing asset allocation as variables and calculates the recommended allocation individually.

Usage example

This method is used to maintain the quality of judgment while reducing daily confirmation work.

CASE A

Portfolio realignment for busy professionals

Users who have multiple accounts in between their main jobs can reduce the frequency of market price checks and still receive notifications only when the allocation bias exceeds a certain level. The decision on whether or not rebalancing is necessary is left to AI, and the user only confirms whether it is possible or not.

once a weekApproximate confirmation frequency 3 indicatorsNumber of notification conditions

CASE B

Strategic decision-making support for expanding your side business

When the income from your side business increases and you need to make a decision on reinvestment, we will calculate the correlation with existing assets and the impact on cash flow. After understanding the risks associated with expansion decisions in advance, you can consider the upper limit of the investment amount.

monthlyRecalculation frequency multiple scenariosEstimated comparison

AI APP 267 development team working on data analysis

The aim is to reduce the distance between data and decision-making.

AI APP 267 provides an analysis platform that combines predictive models and actual data to address the issue faced by investors and sideline workers: ``There is a lot of information, but the materials for making decisions are not organized.'' The final decision is always made by the user himself, and AI plays the role of supporting that decision.

6 asset classes Corresponding analysis target

15 minute intervals Data update frequency

Frequently asked questions

Confirmation regarding reliability and security.

How is the data I enter protected?

Input data such as held assets and transaction history is encrypted during communication and storage. Access privileges are limited to the user's own account and will not be provided to third parties.

How accurate are AI predictions?

Although the prediction model is verified based on historical data, it does not guarantee future market trends. The confidence score is a reference index that indicates the certainty of the prediction, and is designed with the assumption that the final judgment is made by the user himself.

What is the fee structure?

You can start analyzing the basic functions for free, and more detailed allocation proposals and reporting functions are available in paid plans. There is no contract period and you can change your plan as needed.