Scrizena — data analysis and decision optimization platform
Decision optimization

Predictive models to transform your data streams into measurable decisions

Scrizena continuously analyzes market and operating indicators, then provides recommendations classified by risk level. Each performance is published daily.

Access the dashboard Analyze performance
+4.8%
Cumulative net return (30 days)
91.2%
Accuracy of active models
24h
Frequency of publication of reports
4.2M
Data points processed / second
-37%
Average reduction in portfolio risk
128
Predictive models active in production
42ms
Average processing latency
Methodology

From raw data flow to actionable recommendation

Analytical processing follows a fixed and auditable chain. No steps are hidden from the end user.

  1. Ingestion

    Market, operational and transaction data feeds are collected continuously via dedicated API connectors.

  2. Standardization

    The raw data is cleaned, structured and timestamped before any calculation.

  3. Modeling

    Predictive models estimate the probability of each scenario and its associated risk level.

  4. Restitution

    Recommendations are prioritized, documented, and then delivered to the user dashboard.

Three-layer architecture

The analytical pipeline is based on three independent layers: collection, calculation and restitution. This separation makes it possible to isolate a single failure without interrupting the entire system. Each layer logs its own execution logs, which can be viewed from the audit module.

  • REST and FIX API connectors
  • Programmable export in CSV and JSON
  • Compatibility with major brokers and ERPs
  • Two-factor authentication for shared access
Decision engine

Four modules to cover the entire decision-making cycle

Each module operates autonomously and can be activated or deactivated according to the defined risk profile.

Forecast

Predictive analytics module

Evaluates several market scenarios from long time series and identifies significant correlations between variables.

Risk

Risk assessment dashboard

Displays exposure by asset category and reports tolerance thresholds exceeded based on the defined profile.

Alert

Real-time alert system

Notifies any significant discrepancy between the forecast and the observed data, within less than one minute.

Reporting

Automated reporting engine

Generates a structured daily report without manual intervention, archived for later consultation.

Transparency protocol

A performance report published every day, without exception

The structure of the report remains the same from one day to the next. No data is modified after publication.

Example of daily report structure
Date Wallet Daily yield Deviation vs. forecast Status
12/03 Stocks — Model A +0.31% -0.02pt Compliant
12/03 Bond — Model B +0.08% -0.05pt Compliant
12/03 Diversified — Model C -0.12% +0.18pt Under surveillance
The columns and format are fixed. Only the values ​​vary from day to day.

Full traceability

Each decision is recorded with its timestamp, the model version used and the exact state of the input data. This history remains viewable at any time.

Audit standards

The calculation method remains stable over time and can be extracted for independent control. Archived reports are never modified retroactively.

Internal functioning

An infrastructure designed to run without continuous supervision

Models run in the background, regardless of user presence. Risk parameters, once defined, are automatically applied to each new calculation cycle. No manual action is required to keep reports published.

Scrizena — analytical processing and reporting infrastructure
Use cases

Three concrete application contexts

The same decision engine adapts to different objectives depending on the data transmitted.

Analysis of financial markets

The models evaluate the volatility and correlation between asset classes in order to adjust the exposure of a portfolio according to a risk threshold fixed in advance. The recommendations are transmitted before the opening of the sessions concerned.

Calculation frequency
Continuous, streaming market data
Monitored indicator
Exposure by asset class
Exit
Allocation recommendation ranked by risk

Operational efficiency

Operating data (deadlines, costs, error rates) are compared to historical benchmarks to identify persistent discrepancies. The system reports processes whose drift exceeds the configured threshold.

Calculation frequency
Daily, based on consolidated data
Monitored indicator
Operational gap vs reference
Exit
Anomaly report classified by severity

Strategic Growth Forecast

The models project multiple growth trajectories based on historical revenue and cost data. Each trajectory is accompanied by a confidence interval, updated with each new data cycle.

Calculation frequency
Monthly, with interim update
Monitored indicator
Projected Income Trajectory
Exit
Ranked scenarios with confidence interval

Access the dashboard and view the first performance report as soon as it is published

Implementation starts with defining your risk profile, followed by activation of the corresponding models.

Access the dashboard
Commissioned within 48 working hours after validation of the risk profile.