Turn production data into better production decisions.
Capacity, scheduling, downtime and yield — connected to demand and cost so the schedule reflects the business, not just the machine.
What makes this hard today.
The plant produces enormous volumes of data and still schedules on experience. When throughput drops, the cause is debated after the shift rather than identified during it.
Schedules built without visibility of real available capacity
Downtime explained retrospectively, in the morning meeting
Yield loss absorbed into an average and never traced
Production plans disconnected from the demand they serve
The cost of deciding blind.
Capacity is the most expensive asset in the business and the least reversible decision. An hour of unplanned downtime cannot be recovered, and a schedule built on an optimistic capacity assumption fails quietly, late.
Production Intelligence
Veraius reads MES, ERP and machine telemetry together, models real available capacity, and evaluates schedule options against demand, material availability and cost — with the constraint that binds made explicit.
Capacity modelling
Available capacity by line and shift, from actual performance rather than nameplate.
Schedule evaluation
Options compared against demand, materials and cost before committing.
Downtime prediction
Where downtime is likely, and which machine carries the risk.
Yield analysis
Yield loss traced to line, product and process parameter.
Quality drivers
Which parameters correlate with quality outcomes, per line.
Cost per unit
Production cost decomposed so increases can be attributed.
Connect. Understand. Predict. Decide. Act.
The same pipeline runs behind every solution: your systems are connected, the data is put in business context, the outcome is predicted, the decision is reasoned with its sources attached, and the result is carried into workflow.
ERP, POS, MES, WMS, CRM and IoT — into one place.
Operational data related and put in business context.
Demand, stock, production and performance, ahead of time.
Decision models and AI weigh the options with you.
Decisions executed through workflow and automation.
What changes in the way you work.
Schedules rest on measured capacity instead of assumed capacity
Maintenance is planned against risk rather than a fixed calendar
Yield and quality problems are traced to a process, not to a shift
Production decisions stay connected to demand and margin
Where it is used in practice.
Weekly production planning
What to produce on which line, given demand and material coverage.
Capacity risk review
Where the coming schedule exceeds realistic available capacity.
Downtime investigation
Which machines and conditions precede unplanned stoppages.
Cost variance analysis
Why unit cost moved, decomposed into its contributing factors.