07 – Core Service
AI & predictive analytics
Most companies that want AI need a working data pipeline first. We start with the business problem, build models that solve it, and deploy them where they actually get used – not where they look good in a slide.
Common use cases
Customer churn prediction and retention modelling
Customer segmentation and recency-frequency-monetary analysis
Demand forecasting and inventory optimization
Anomaly detection in transactions or operations
Language-model internal tools and document automation
Ideal for
CDOData leadCTO
Explore AI solutions
07
Machine learning stack
Python
Scikit-learn
XGBoost
TensorFlow
Pandas / NumPy
AI platforms
OpenAI API
Vertex AI
AWS SageMaker
Databricks
How it works
1
Define the problem
2
Train & validate
3
Deploy & measure