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Azure ML Integration

Predictive Intelligence with Azure ML

DuluthPath leverages Azure Machine Learning to train, deploy, and operationalize predictive models on your ERP and financial data — from demand forecasting to anomaly detection.

ML Pipeline Status

RUNNING
Data Ingestion2.3s
1.2M rows
Feature Engineering8.7s
847 features
Model Training4m 12s
XGBoost + LSTM
Validation1.1s
R2=0.94
Deployment...
AKS endpoint
LIVE SIMULATION

Azure ML Model Demonstrations

Interactive previews of production ML models trained on enterprise data

Demand Forecast — XGBoost + LSTM Ensemble

95% confidence interval shown. Model retrained weekly on Azure ML Compute.

R2 = 0.94 | MAE = 312
  • Actual
  • Lower Bound
  • Predicted
  • Upper Bound
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ML Capabilities

Azure ML + DuluthPath

AutoML

Automated model selection and hyperparameter tuning on enterprise data.

  • Automated feature engineering
  • Multi-algorithm tournament
  • Explainable AI (SHAP values)
  • Model versioning & lineage

Real-Time Scoring

Low-latency inference endpoints on Azure Kubernetes for live predictions.

  • Sub-100ms inference
  • Auto-scaling endpoints
  • A/B model testing
  • Canary deployments

Responsible AI

Built-in fairness, interpretability, and compliance for regulated industries.

  • Bias detection & mitigation
  • Model interpretability dashboards
  • Data drift monitoring
  • Compliance audit trails
Architecture

Azure ML Pipeline Architecture

01

Data Sources

SAP, Oracle, Salesforce via DuluthPath connectors

02

Azure Data Factory

ETL orchestration with data quality gates

03

Feature Store

Centralized feature repository with versioning

04

Azure ML Studio

AutoML training, validation, and deployment

05

Inference API

Real-time & batch predictions via AKS endpoints

Ready to Deploy Predictive Intelligence?

See how DuluthPath + Azure ML delivers production-grade predictive models on your enterprise data.