NeuroView AI continuously analyzes market data and the best performing algorithmic strategies, then returns allocation recommendations adapted to your risk profile, without promise of guaranteed return.
The platform combines multi-criteria analysis, risk modeling and replication of effective strategies to transform a large volume of data into actionable decisions.
Market, on-chain and macroeconomic data feeds are continuously aggregated and weighted to identify relevant signals among statistical noise.
Each recommendation incorporates an estimate of expected volatility and a stress scenario, in order to place the decision within an explicit risk range.
You access a continuous ranking of algorithm-driven strategies and can replicate their allocation, with permanent oversight of the positions followed.
Allocation suggestions take into account your investment horizon and stated risk tolerance, without applying a single model to all profiles.
Each recommendation results from a sequence of documented treatments, from cleaning the raw data to readjusting the model based on the observed results.
Market, historical and alternative data is ingested and then cleaned to remove outliers and duplicates.
Statistical and machine learning models estimate the likely trajectories of assets tracked over different horizons.
Each model is confronted with historical stress scenarios before being allowed to produce recommendations in real conditions.
The results are translated into readable allocation proposals, accompanied by their confidence level and the assumptions made.
Actual performance is compared to projections, and model parameters are revised when the deviation exceeds a defined threshold.
The scenarios below illustrate representative uses. The indicators displayed are categories followed by the model, not guaranteed results.
Monitoring of algorithmic strategies classified by regularity of performance, with the possibility of replicating an allocation while maintaining control over exposure thresholds.
Analysis of currency and rate exposure to adjust short- and medium-term liquidity investment decisions.
Integration of model signals in addition to existing management, for purposes of cross-checking or diversification of decision sources.
Consolidated vision of risk on a multi-asset portfolio, with regular feedback intended for decision-making in the investment committee.
NeuroView AI was built around a simple principle: a recommendation is only valuable if it can be explained. Each decision displayed on the platform is accompanied by its hypotheses, its confidence level and its validity horizon, so that the user retains control of their final decision.
The team favors a gradual evolution of models, tested before any deployment, rather than a promise of immediate performance.
Models are trained on historical market data and periodically re-evaluated using recent data to limit the gap between projections and actual conditions.
The platform relies on market data, on-chain data for the digital assets concerned, as well as public macroeconomic indicators. No unverifiable data is included in the model.
You select a strategy from among those followed by the platform, classified according to their regularity of performance and their risk profile. Position replication is carried out according to allocation rules that you define, with the possibility of interrupting tracking at any time.
Standard access is via the web interface, with no development required. API integration is available for structures wishing to connect their own monitoring tools.
The platform produces recommendations and, in copy-trading mode, replication proposals. The final validation and setting of risk thresholds remain under your control.
A technical demonstration allows you to explore the methodology, the data used and an example of recommendation applied to a scenario close to your context.