Qorvethan brings together your depots, wallets and trading accounts in one dashboard and evaluates the data using AI models from multiple stock exchanges - consistently, comprehensibly and in real time.
The dashboard consolidates positions, order history and risk metrics from connected exchanges in a structured view - without manual comparison between platforms.
Anyone who invests in multiple asset classes or across different exchanges usually manages multiple logins, export formats and notification systems in parallel. Every switch between platforms costs time and increases the risk of delaying the perception of relevant market movements.
Qorvethan was developed to resolve this fragmentation: All connected accounts are brought together in a uniform data structure so that evaluations are carried out on a consistent basis.
The platform combines data collection, modeling and risk management in a common infrastructure.
The models work with historical and ongoing market data and identify recurring patterns using pattern recognition. Results are presented as probability ranges, not as firm commitments - reflecting the actual uncertainty of market forecasts.
Connected accounts are continuously compared via standardized interfaces. By minimizing latency in data transfer, position changes are available promptly in the central dashboard, instead of only after manual export.
Position sizes, volatility and correlations between asset classes are continually assessed. If a portfolio exceeds defined thresholds, a message appears on the dashboard before the deviation becomes relevant.
The cycle of recording, optimization and recommendation is transparent and understandable - including the underlying database.
Accounts and trading venues are connected via secure interfaces. Price, order and inventory data flow into a standardized data structure.
The forecast models are constantly compared and readjusted with new data. Deviations between the prediction and the actual course are included in the next calculation.
The result is displayed as a concrete recommendation with the underlying database so that the decision remains comprehensible - not as an unsubstantiated black box statement.
The following examples describe how working users use central analysis in their everyday lives.
Automated overview of multiple income-oriented positions without having to check each platform individually.
Correlation analyzes show how strongly individual asset classes in the portfolio actually depend on each other.
Signals and risk metrics are available centrally when the market opens, instead of being spread across multiple tabs.
Data processing is carried out in accordance with the requirements of the GDPR. Access data to connected exchanges is stored in encrypted form, and only read API permissions are used for the connection, as long as the respective exchange supports this.
Common trading venues and depository providers that provide a standardized programming interface are supported. The connection takes place via the respective official API, without access data being passed on to third parties.
The conditions depend on the number of connected accounts and the scope of functions. You will receive details about the current price structure after requesting analysis access.
Request analytics access and see how your connected accounts can be displayed in a dashboard.
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