Machine Learning & Analytics
Predictive models, anomaly detection and recommendation systems to translate data into actionable insights and operational improvements.
What we build
We convert messy data into reliable models and dashboards that help teams forecast, detect issues, and personalize customer experiences. Production-ready pipelines with monitoring and retraining loops included.
Key features
- Time series forecasting & trend prediction
- Anomaly & fraud detection pipelines
- Recommendation & personalization engines
- Feature engineering & model explainability
- AI-driven dashboards & BI integrations
Perfect for
- Inventory & demand forecasting
- Transaction fraud detection
- Personalized product recommendations
- Churn prediction & customer segmentation
FAQs
How quickly can you build a pilot model?
A focused pilot (one use case, cleaned dataset) typically takes 3–6 weeks including testing and validation.
What data do you need for forecasting?
Historical time-series data, business context, and any external signals (e.g., promotions, seasonality) are ideal for accurate forecasts.
Do you provide dashboards?
Yes — we deliver BI dashboards and integrate model outputs with your analytics stack (Looker, Power BI, Grafana, etc.).