Comment mes données sont-elles protégées ?

Les données sont chiffrées au repos et en transit. L'accès aux informations financières est segmenté par rôle et chaque consultation est journalisée.

Quelles sont les limites de l'automatisation ?

Le moteur exécute uniquement les règles validées par l'utilisateur. Toute modification du profil de risque ou tout seuil dépassé déclenche une confirmation manuelle avant exécution.

Quelles sources de données sont utilisées ?

Les revenus déclarés par les plateformes partenaires, les relevés bancaires connectés et des indicateurs de marché public alimentent le modèle. Aucune donnée n'est partagée avec des tiers à des fins commerciales.

Perle Chainelle — predictive platform revenue analytics dashboard

Data Intelligence Platform

Stabilize your additional income through predictive analysis.

Perle Chainelle aggregates your business data, models volatility and adjusts your risk exposure continuously, without spreadsheets or estimates on sight.

Start analysis See how it works

Observation

Manual risk management no longer tracks platform revenue variability.

Drivers, delivery people and freelancers work irregular weeks. Spreadsheets and rough estimates are no longer enough to anticipate business dips.

Without a structured model, each savings or investment decision is based on an intuition that is difficult to verify after the fact. The gap between perceived income and actually available income accumulates, often without being measured.

Perle Chainelle — visualization of the weekly variability of a platform income

Typical weekly distribution of platform income, before modeling by Perle Chainelle.

Mechanism

Predictive models and an adaptive risk engine, not a black box.

Real-time analysis

Income streams, expenses and market indicators are processed continuously. Any significant deviation is reported within an hour of its occurrence.

Adaptive risk tolerance

The model learns from your past decisions and automatically adjusts exposure thresholds, without repeated questionnaires or manual settings.

Automated execution

Arbitrations validated by your risk profile are executed according to predefined rules, with complete traceability of each operation.

Methodology

A verifiable data intelligence process, without staged testimony.

Aggregation

Data from your activity platforms and your financial accounts are centralized in a single, verified and time-stamped format.

Analysis

Predictive models identify trends, seasonality and volatility factors specific to your business.

Optimization

Recommendations are classified by impact and risk level, then subject to validation before any automated execution.

Use cases

Two profiles, the same risk management discipline.

Income smoothing for self-employed workers

A delivery driver with variable income defines a monthly minimum threshold. The system automatically distributes a reserve during favorable weeks and releases it during low weeks, according to rules set in advance.

Applied logic

Floor threshold → automatic reserve

Portfolio protection for independent investors

An individual investor combines their platform activity with a portfolio of assets. The risk engine reduces exposure to volatile assets when earned income falls, in order to limit the accumulation of losses.

Applied logic

Declining income → reduced exposure

Technical questions

Security, automation limits and data origin.

How is my data protected?

Data is encrypted at rest and in transit. Access to financial information is segmented by role and each consultation is logged.

What are the limits of automation?

The engine only executes rules validated by the user. Any modification of the risk profile or any threshold exceeded triggers a manual confirmation before execution.

What data sources are used?

Income declared by partner platforms, connected bank statements and public market indicators feed the model. No data is shared with third parties for commercial purposes.