Ronaviraxa applies predictive models to distribute a freelancer's idle capital between contracts, adjusting the risk according to the real cash flow of each professional profile.
The problem
Ronaviraxa was designed to operate in the background: while the professional concentrates on his work, the system evaluates market conditions and adjusts capital allocation according to user-defined risk parameters.
Methodology
The Ronaviraxa engine combines financial data ingestion, real-time predictive models and community verification before executing any recommendations.
Market indicators, available liquidity and the income schedule declared by the user are consolidated.
Models trained with historical series estimate risk-return scenarios in short and medium-term windows.
The system proposes a capital allocation adjusted to the configured risk limits, not to a generic profile.
Each recommendation executed is recorded in public performance logs, reviewable by the user community.
Algorithmic transparency
Instead of isolated success stories, Ronaviraxa publishes an auditable history of decisions and their subsequent performance, so that each user can evaluate the system with their own data.
Each move suggested by the algorithm is linked to its actual result, without subsequent curation. This makes it possible to compare the projected performance with that actually obtained.
Platform
Each function is aimed at reducing risk exposure without requiring constant manual monitoring.
User-configurable exposure limits, automatically applied before any portfolio adjustment is executed.
Market and personal liquidity indicators are updated continuously, without depending on periodic manual reviews.
Approved recommendations are applied according to predefined rules, reducing the time between analysis and action.
Parameters are adjusted based on the declared income schedule, not a standard investment profile.
Frequently asked questions
Income and liquidity data are used solely to calibrate the user's predictive models. Access to this information is restricted to analysis processes and is not shared with third parties outside the operation of the platform.
Yes. The user defines the minimum level of liquidity that must be kept available at all times. Capital allocations respect that limit before proposing any additional moves.
The model combines market variables with the declared income schedule and user-configured risk limits. Final strategic decisions, such as the level of exposure allowed, always remain under the control of the user.
Integration with common freelance workflows does not require manually migrating data or interrupting ongoing projects.
Start free analysisAccess to public performance logs from the first login.