Naxelo Rivu — predictive portfolio analysis interface

Institution-grade predictive analytics, set up in less than 60 seconds

Naxelo Rivu connects your portfolio to an AI-driven decision engine designed to process massive volumes of data and reduce human error in your daily arbitrages.

Decision engine

An engine designed to reduce uncertainty, not to amplify it

Each recommendation results from structured processing of market data, not from an isolated prediction.

Real-time multi-factor analysis

The engine cross-references dozens of variables — volatility, liquidity, sector correlations — to identify configurations with asymmetric risk.

Calibrated stochastic models

Each recommendation is based on continuously updated probabilistic simulations, rather than static rules.

Integrated risk management

Exposure thresholds and maximum loss scenarios are recalculated with each significant market movement.

Minimum execution latency

The infrastructure is sized to transmit signals with a processing time compatible with active trading.

In practice, this means less time spent manually cross-referencing dashboards and more time devoted to strategic decisions. The engine does not replace your judgment: it structures the information on which it is based.

Getting started

Three-step configuration, without prolonged manual intervention

The “one-click setup” principle is based on a secure connection and risk parameters defined only once.

01

Secure connection

Link your trading account via an encrypted API, without transmitting clear identifiers.

02

Calibration of the risk profile

Indicate your risk tolerance and capital constraints; the engine adjusts its parameters accordingly.

03

Motor activation

Predictive analysis starts immediately and the first recommendations are available in less than 60 seconds.

The speed of startup does not eliminate the need for a calibration phase: the risk parameters defined in step 2 remain modifiable at any time, without requiring complete reconfiguration.

REST API FIX protocol Real-time webhooks OAuth 2.0 authentication
Data processing

A processing capacity designed for institutional data volumes

The dashboard aggregates market feeds in the form of correlation maps and volatility curves, updated as new data arrives. The objective is not visual density, but the readability of areas of tension.

Predictive models combine multiple approaches—time series, supervised learning, and historical backtesting—rather than a single algorithm. This combination limits dependence on a single market regime.

Risk management remains central: each recommendation is accompanied by a maximum loss scenario and a suggested position size, consistent with the profile defined during the initial calibration.

Naxelo Rivu — visualization of market data and predictive models
Methodological transparency

Understand the mechanisms rather than suffer them

An automated decision system only has value if its logic remains verifiable by the user.

General operation of the algorithm

The engine is based on a set of models trained on market histories, re-evaluated periodically as new data becomes available. User-defined risk parameters act as constraints on the generated recommendations, not simple display preferences. A quantitative team monitors performance gaps between forecasts and observed results, and adjusts model calibration when these gaps exceed defined tolerances.

Safety standards

  • TLS encryption in transit on all data exchanges
  • Encryption of sensitive data at rest
  • Two-factor authentication for account access
  • Separation of production and test environments
  • Redundant backups of wallet configurations

Performance tracking

Processing times and infrastructure availability are continuously monitored. Deviations in latency or unavailability are recorded in a searchable log, so that the reliability of the system remains verifiable and not simply asserted.

Frequently asked questions

Things our users check before configuring the engine

Does the engine execute orders automatically, or does it only provide recommendations?

By default, the engine produces recommendations accompanied by a confidence level and a risk scenario. Automated execution can be enabled separately, once the risk profile has been validated.

What market data powers the predictive models?

The models rely on price histories, volatility indicators and liquidity measurements from marketplaces connected via the API. The user's proprietary data is not shared between accounts.

How is the risk profile determined?

It is based on the parameters provided during calibration — loss tolerance, trading horizon, capital constraints — combined with thresholds dynamically recalculated according to observed market conditions.

What is the latency between a market signal and a displayed recommendation?

The infrastructure is designed for rapid processing of incoming flows, with a latency objective compatible with the needs of active trading. The exact latency depends on the volume of data processed at any given time.

Are my login credentials stored in clear text?

No. Login to trading accounts is done via encrypted authentication tokens, without storing credentials in readable form.

Can I stop the analysis at any time?

Yes. Disconnecting the engine is immediate and does not affect positions already opened, which remain managed directly from your usual trading platform.

Other technical or strategic questions? Visit our help center.

Configure your analytics engine in less than 60 seconds

Connect a trading account, define your risk profile, and let the engine produce its first recommendations.

No credit card required to start setup.