01
Sales forecasting
Anticipates future sales to adjust stock and resources accordingly.
- Forecasts by product/region
- Stock adjustment
- Automatic alerts
Expertise
ML · Data · Prediction
Approach
Data audit → POC → Prod
Deployment
4–10 weeks
Languages
FR · EN · NL
Machine Learning
Turn your data into useful predictions
Fronx builds machine learning models trained on your data to anticipate trends, detect anomalies and improve your decisions.
95%+
Target accuracy
EU
Data hosted
4–10
Weeks to deploy
100%
On your data
Machine Learning
FronxSolutions
Your data has value
Predictions grounded in your reality
No generic model: every solution is trained on your own business data.
- Analyzes your historical data to identify trends
- Predicts future behavior with a custom model
- Detects anomalies before they become problems
- Keeps improving as new data comes in
Pythonscikit-learnTensorFlowPandas
Features
From raw data to decision
Collection, training, validation — a complete pipeline built for reliability.
Machine Learning
6 features, one platform
Drag the globe to explore. Click a glowing node to read its description.
Use cases
Real-world use cases
02
Customer scoring & segmentation
Identifies the most profitable customers and those at risk of churning.
- Risk score
- Dynamic segments
- Targeted actions
03
Anomaly detection
Monitors your data flows to spot fraud, failures or errors.
- Real-time alerts
- Customizable thresholds
- Incident history
04
Demand forecasting
Plans human and material resources based on reliable forecasts.
- 30/60/90-day forecasts
- Export to your tools
- Continuous updates
Our process
Fronx AI method
- 01
Use case and ROI audit
- 02
Prototype with your real data
- 03
CRM, ERP, API integration
- 04
Deploy, train and monitor
Benefits
Why FronxSolutions?
Useful integrated AI
Connected to your existing tools.
Measurable ROI
KPIs defined from day one.
Fast POC
Validation in 2–3 weeks.
Data security
EU hosting, encrypted APIs.
Integrations
Connected to your data sources
Compatible with your existing databases, data warehouses and BI tools.
- PostgreSQL
- BigQuery
- Snowflake
- Power BI
- Excel/CSV
Technologies
- Python
- scikit-learn
- TensorFlow
- PyTorch
- Pandas
- Jupyter
FAQ
It depends on the use case, but a few months of history is often enough for a first workable model.
It varies by use case — we validate accuracy on your real data before any deployment.
Yes — European hosting, no sharing with third parties, GDPR compliant.
A validation POC takes 2 to 3 weeks; full deployment, 4 to 10 weeks depending on complexity.
Yes, a model is periodically reassessed to stay accurate as your data evolves.
