Fortuinheim analyzes your income patterns and market data in real time and gives freelancers concrete, risk-aware recommendations to generate capital returns during quiet periods.
Discover the possibilitiesFreelancers generally do not have a fixed monthly income. There can be weeks to months between two assignments, while fixed costs continue. Without insight into patterns, it is difficult to determine how much buffer is needed and when available capital can be used responsibly.
Most financial tools are built for fixed salaries and do not take this irregularity into account.
Fortuinheim combines historical turnover data with current market signals. The system recognizes seasonal patterns in your order flow and uses this to calculate when capital is available for controlled growth, without affecting the operational buffer.
The model weighs historical cash flow data, outstanding invoices and macro indicators against each other. Each recommendation is given a risk score, so you always know the underlying assumption before you make a choice.
The functionality is built around prediction, risk management and timely recommendations. Each part can be traced back to verifiable data.
The model learns from previous billing cycles, seasonality within your sector and the average lead time between assignments. On this basis, it paints a realistic picture of upcoming quiet periods, well before they occur.
The forecast is updated weekly with new data, so that the estimate changes with your actual situation.
Before capital is recommended for deployment, the system checks the desired buffer, current obligations and market volatility. Recommendations that would affect this buffer are not shown.
As soon as market conditions or your own cash flow change, the system recalculates the recommendation. You will only receive a notification when an adjustment is actually relevant.
Fortuinheim publishes the results of its recommendations publicly. Any user can verify the historical accuracy of the model, regardless of marketing claims.
Illustrative representation of the log format. The complete, up-to-date overview of timestamps is available in the platform.
Each recommendation is recorded with a time stamp, underlying assumption and the achieved result. This combination makes it possible to check afterwards whether the logic held up, instead of just showing the end result.
Users can have their own results anonymously included in the public log. This creates a picture that is not only based on internal test data, but on a growing number of independent applications in practice.
Fortuinheim is designed to complement your existing accounting and banking needs, not as a replacement. The platform links to the data sources you already use and adds a layer of predictive analysis.
The methodology is based on reproducible statistical models. Assumptions and limitations are explained with each recommendation, so that the outcome remains easy to follow.
The design is deliberately limited to three steps, with minimal time investment for the user.
You link invoicing and banking data via a secure connection. The system processes historical data to create an initial baseline of your income pattern.
The model is tailored to your sector, work rhythm and risk appetite. This step determines how cautious or broad future recommendations will be.
From that moment on, the platform continuously recalculates based on new data. Recommendations are adjusted as soon as your actual situation deviates from the previous forecast.
Connections to banking and billing data are made via encrypted, read-only links. Fortuinheim has no ability to transact on your behalf; the platform only provides analysis and advice.
Data is used to train your personal prediction model and, after anonymization, to improve overall model accuracy. You can view what data has been stored at any time and have it deleted.
Each recommendation is based on a combination of historical patterns, current market data and an explicit risk score. The model shows which factors were given the most weight, so that the recommendation is never a black box.
Fortuinheim does not replace financial advice, but adds a layer of data support to decisions that you would otherwise make based on gut feeling. Before connecting data, see how the model performs.