Build and deploy machine learning models without writing code
Intelecy gives process experts a guided way to create models for the problems they understand best. Teams can choose use-case templates, select process data, train models, validate behavior, deploy to production, and monitor performance without depending on scarce data science resources for every iteration.
Templates and governance
Anomaly detection
Learn normal behavior and flag deviations in live process data.
Forecasting
Predict future process values, quality indicators, or asset behavior.
Prescriptive recommendations
Suggest setpoints or actions that keep the process in a better operating window.
Validation and monitoring
Track model quality, drift, ownership, and production status.
How it fits into the full Intelecy workflow
- 01
Connect relevant data through secure industrial integration.
- 02
Use Data Explorer to understand the historical and live process context.
- 03
Build, validate, deploy, and monitor the relevant model or workflow.
- 04
Route outputs to dashboards, alerts, recommendations, or controlled automation.
- 05
Measure the impact with verified operational KPIs.
Proof
Proof requirementAdd one relevant customer quote, screenshot, or mini story that proves this capability in a real industrial context. If proof is from an adjacent industry, label it clearly.
See this capability on a real process workflow
In a demo, Intelecy can show how this capability fits into your data, your team, and your operational targets.