What We Build
From demand forecasting to customer behavior analysis, we build production-ready predictive models that deliver measurable business value.
Demand Forecasting
Predict future demand with ML models that optimize inventory and reduce stockouts
Fraud Detection
Real-time anomaly detection to identify fraudulent transactions and prevent losses
Customer Analytics
Predict churn, segment customers, and personalize experiences with behavioral models
Real-World Use Cases
See how companies are using Data Science to make smarter, data-driven decisions
Demand Forecasting for Retail
ML forecasting model predicts product demand across 500+ SKUs, reducing stockouts by 35% and cutting excess inventory by $2.4M annually.
- 92% forecast accuracy
- 35% reduction in stockouts
- $2.4M inventory savings
Real-Time Fraud Detection
Anomaly detection system analyzes transactions in real-time, identifying fraudulent patterns with 94% accuracy while reducing false positives by 60%.
- 94% fraud detection accuracy
- 60% fewer false positives
- $8.5M in prevented losses
Customer Churn Prediction
Predictive model identifies at-risk customers 30 days before churn, enabling proactive retention campaigns that reduce churn by 28%.
- 89% churn prediction accuracy
- 28% reduction in churn rate
- 30-day early warning system
Predictive Maintenance
IoT sensor data analysis predicts equipment failures 7 days in advance, reducing unplanned downtime by 45% and maintenance costs by $1.2M annually.
- 87% failure prediction accuracy
- 45% reduction in downtime
- 7-day advance warning
Our Technology Stack
We use industry-leading data science tools and frameworks to build production-ready ML models
Programming Languages
Python, R, SQL, Scala
ML Frameworks
scikit-learn, XGBoost, LightGBM
Data Processing
Pandas, Spark, Dask, NumPy
Visualization & BI
Tableau, PowerBI, Plotly, Matplotlib
Ready to Unlock Your Data's Potential?
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