Artificial intelligence at the service of your additional investment income
Soreli Zurem continuously processes volumes of market data that manual analysis cannot cover, to provide backtested strategies tailored to a variable self-employed income.
Soreli Zurem continuously processes volumes of market data that manual analysis cannot cover, to provide backtested strategies tailored to a variable self-employed income.
Self-employed and platform workers already experience irregular income from week to week. Adding active portfolio management without a suitable tool multiplies the risk of timing errors and excessive exposure.
Financial markets produce a volume of data every day — prices, trading volumes, macroeconomic indicators, sentiment signals — that manual monitoring cannot process with the same speed or consistency as an automated system.
Each strategy proposed by Soreli Zurem goes through the same four steps, from processing raw data to calibrated execution, in order to keep a reproducible process rather than one-off decisions.
Prices, volumes, macroeconomic indicators and volatility signals are collected continuously from structured sources.
The models identify correlations and recurring patterns across histories of multiple market cycles.
Each recommendation is adjusted according to defined risk thresholds, without seeking isolated maximum returns.
Strategy adjustments are applied as soon as market conditions change the initial parameters.
Soreli Zurem's tools are designed to work together, each addressing a distinct stage of the investment decision.
Projection of market scenarios based on historical data and macroeconomic variables updated daily.
Dynamic calculation of portfolio risk exposure, with configurable alert thresholds according to your financial capacity.
Progressive adjustment of allowances according to the evolution of your additional income, without starting from a fixed strategy.
Each strategy is first simulated on historical market data covering several phases of volatility, before any real application. This backtesting step makes it possible to measure the theoretical behavior of a strategy under conditions already observed.
The backtested results are documented and viewable, and each model update is subject to a new validation phase before replacing the previous model.
Illustrative representation of a backtested simulation — non-contractual data
Connections to the platform are end-to-end encrypted and account access requires strong authentication. Soreli Zurem does not move your assets without explicit action on your part.
The interface presents recommendations and risk levels in a readable manner, without requiring mastery of the underlying statistical models. However, an understanding of the basics of investing is still recommended.
The models rely on structured market feeds, public macroeconomic indicators and historical pricing. No third-party personal data is used in training the models.