From production data to a better operating decision.
Intelecy turns live industrial data into early warnings, forecasts, recommendations and approved closed-loop action. The workflow starts with a measurable operational problem, not with a generic AI project.
Start with the operational problem.
Define the recurring loss, constraint or risk in the KPI language the plant already uses.
Agree the process in scope, the data available, the people who own the outcome and what success would mean.
Typical starting points: unplanned downtime, throughput constraint, quality variation, yield loss, energy intensity or recurring abnormal behaviour.
Connect to the existing plant stack.
Use the Intelecy Gateway to connect qualified historians, OPC-UA sources and control systems, or use supported cloud data sources.
The objective is to make the required production context available without turning the engagement into a wider rip-and-replace data programme.
Learn from industrial time-series behaviour.
Intelecy develops and operates models suited to multivariate production processes: anomaly detection, forecasting and prescriptive optimisation.
Process expertise remains essential. Operators and engineers help define normal behaviour, meaningful events, practical constraints and the actions the plant can take.
Put the result where action can still change the outcome.
An alert is useful only when it reaches the right person with enough context and time to respond.
Intelecy connects model output to operational workflows through alerts, forecasts, recommendations and investigations designed around the decision to be made.
Close the loop where it is justified and approved.
Selected recommendations can progress to closed-loop optimisation when the process, business case, control architecture and governance support it.
Objectives, variables, setpoints, approved limits, safety interlocks, customer supervision, audit trail and rollback are defined before action is automated.
Know what changed, what it was worth and what to do next.
Operational improvement should be connected to an agreed baseline and attribution method. Intelecy distinguishes potential, identified, realised and verified value so plants can make better renewal, expansion and prioritisation decisions.
Intelecy can run it — or your team can.
Choose a managed service when the plant wants the outcome without taking on specialist model operations. Choose customer operation when an internal team is ready to build and maintain the capability. Both paths use the same platform foundation.
Intelecy operates the AI end-to-end — connection, models, monitoring and value tracking — delivering operational outcomes as a service.
Your engineers own models end-to-end on the same platform, with Intelecy supporting enablement and governance.
Start with one measurable production problem.
A qualified starting point has a recurring operational issue, usable production data, a named process owner and a credible path to operational action.