Machine Learning

Predictive Analytics & Forecasting

Predictive models are only useful if they drive decisions. We build forecasting and prediction systems from data through to the business workflow that acts on the output: connecting demand forecasts to inventory systems, churn scores to retention campaigns, and risk scores to underwriting decisions.

85%

Avg Forecast Accuracy

28%

Inventory Cost Reduction

35%

Churn Reduction for Clients

What We Deliver

Predictive Analytics & Forecasting Services

Practical, production-ready work — not proofs of concept that never make it to real users.

Demand Forecasting

Time series and ensemble models for product demand, resource capacity, and revenue forecasting with confidence intervals.

Churn Prediction

Customer retention models that score propensity to churn and surface actionable signals for your retention team.

Risk Scoring

Credit, fraud, and operational risk models that provide decision-ready scores with explainable contributing factors.

Anomaly Detection

Statistical and ML-based anomaly detection for fraud signals, system failures, and unusual business patterns.

How We Engage

Common Engagements

01

Retail Demand Forecasting

SKU-level demand forecasting integrated into an inventory management system to automate replenishment orders.

02

SaaS Churn Prediction

Customer health scoring model that surfaces at-risk accounts to the customer success team three months before cancellation.

03

Credit Risk Scoring

Alternative data credit model for a lending platform serving customers without traditional credit histories.

04

Predictive Maintenance

Equipment failure prediction model using sensor telemetry to schedule maintenance before breakdowns occur.

Why InnovTen

What You Can Count On

  • Models tuned to your specific data distribution rather than generic benchmarks
  • Output integrated into systems your teams already use for decisions
  • Confidence intervals and uncertainty estimates to support risk-aware decisions
  • Feature importance explanations that business stakeholders can interpret
  • Regular retraining and performance review to maintain accuracy over time

Technologies We Use

Python Scikit-learn XGBoost LightGBM Prophet Statsmodels Snowflake dbt Airflow

Ready to Get Started?

Tell us about your project and we'll put together a practical path forward.

Talk to Our Team