Analyze over 500 trading pairs simultaneously with AI models designed to reduce risk and bring precision to strategic decision making.
Each component of Caudaris IA is designed to reduce the distance between the emergence of a market pattern and the generation of an actionable alert.
Processing of data from more than 500 sources in milliseconds, aimed at detecting correlations and patterns not evident in manual analysis.
Predictive models that estimate the expected volatility of an asset before it translates into an effective loss in the portfolio.
Cloud infrastructure sized to sustain high query frequency without degrading response times during volume spikes.
The process is divided into three different stages, each independently auditable, without a black box or hidden steps between the signal and the recommendation.
Direct connection to the main exchanges and global financial feeds, with normalization prior to any analysis.
Market noise filtering using deep learning neural networks trained on historical and real-time series.
Delivery of actionable recommendations and risk alerts, classified by statistical confidence level.
The Caudaris IA interface eliminates decorative elements. Each panel shows only liquidity, volume and structural trend, without additional layers that distract from reading the data.
The technical team periodically reviews the layout of each module to maintain low reading times, even in high-frequency operating sessions.
The system adapts to different operating horizons, from high-frequency execution to medium-term portfolio management.
Optimization of inputs and outputs based on statistical probability calculated on each analyzed pair.
Assisted rebalancing through correlation analysis between assets in real time.
Integration of macroeconomic and news data to anticipate trend changes before they are reflected in the price.
Direct answers on latency, integration and compatibility, aimed at teams evaluating the incorporation of Caudaris IA into their workflow.
Proximity servers and a microservices architecture are used, with the aim that the data reaches the decision system before the market incorporates it in a generalized way.
Yes. Integration is offered via REST API and WebSockets, designed for proprietary trading systems and for data flows already existing in the client's infrastructure.