Classic Machine Learning (Robust & Explainable)
Where oversized AI models fail and generate unnecessary computational costs, we rely on high-performance, classic ML methods:
- Predictive Pricing
- Automatic, dynamic pricing systems with significantly reduced error rates.
- Anomaly Modeling
- Identification of suspicious transactions and data errors using Isolation Forests and quantitative algorithms.
- Classification & Prediction
- Customer segmentation and lead generation using highly precise decision trees (Decision Trees, XGBoost, Random Forest Classifiers).
- Clustering & Segmentation
- Unsupervised pattern recognition and data segmentation via K-Means, DBSCAN, and hierarchical clustering for deep customer analytics and process optimization.