Machine Learning · Azure & Dynamics 365
ML That Turns
Data Into Decisions
Years of data sit unused in your systems.
Forecasts run on gut feel and last quarter.
Patterns that predict failure go unseen.
RADIN puts your data to work.
The real problem
– Demand planning that reacts instead of predicts.
– Equipment failures that look random but are not.
– Inventory carried too high or run too thin.
– Historical data collected and never modeled.
– Decisions made on averages, not patterns.
Machine learning only matters when it turns your history into a decision you can act on.
RADIN builds and trains models on Microsoft Azure and Dynamics 365 using your own operational data. Demand, failure risk, and inventory become forecasts your teams can trust, and the models keep learning as new data arrives.
✔ What RADIN ML delivers
Models Built on Your Reality
01
Demand Forecasting
Predict orders from your real sales history so production and purchasing plan ahead, not behind.
02
Predictive Failure
Score equipment risk from signal and service data to act before a line goes down.
03
Inventory Optimization
Right-size stock against forecasted demand to protect margin and free up cash.
04
Trained on Your Data
Models learn from your operation, not a generic benchmark, so predictions fit your plant.
05
Continuous Learning
Models retrain as new data lands, staying accurate as your business shifts.
06
Decisions, Not Dashboards
Output lands as a clear recommendation your teams can act on, not another chart.
16+
Years of Dynamics 365 data expertise
24/7
Models scoring in the background
60–90
Days to a trained model
∞
Retraining as data grows
✔ HOW RADIN delivers it
From Raw Data to Reliable Forecast
RADIN builds ML as an operational asset. Each step moves your data closer to a decision you can stand behind.
01
Prepare
Clean and connect your historical data into a foundation models can learn from.
02
Train
Build and validate models on your operation using Azure Machine Learning.
03
Deploy
Put predictions inside Dynamics 365 where your teams already work.
04
Refine
Retrain on new data so forecasts stay accurate as conditions change.
✔ Where it shows up
Where ML Shows Up in Your Operation
A predictive layer that turns the data your systems already hold into forward-looking decisions.
01
Demand & Sales
Forecast order volume and seasonality to plan capacity with confidence.
02
Maintenance
Predict equipment failure from telemetry and service records before it happens.
03
Inventory
Optimize reorder points and safety stock against predicted demand.
04
Finance
Forecast cash flow and margin from operational patterns, not spreadsheets.
05
Supply Chain
Anticipate lead-time risk and vendor variability before it hits a schedule.
06
Quality
Predict defect risk from process data to protect yield and reputation.
Questions
FREQUENTLY ASKED
QUESTIONS
Do we have enough data for machine learning?
Most manufacturers have more usable history than they realize. RADIN assesses what you have and builds models around the data that carries real signal.
Where are the models built and run?
On Microsoft Azure and connected to your Dynamics 365 environment, secured under your access controls and kept current as data grows.
Is this a black box we cannot trust?
No. RADIN validates every model against real outcomes and delivers predictions with the context behind them, so teams understand what drives a forecast.
How is this different from AI?
AI handles language and assistance in the moment. Machine learning finds patterns in your history to predict what comes next. RADIN uses each where it fits.
Who governs it after launch?
RADIN retrains and monitors models with a hybrid US and offshore team, so accuracy holds without adding load to your staff.
Put Your Data to Work
A free review shows where machine learning can turn your history into forecasts your teams will trust.
