COREGRIT
CoreGrit — Manufacturing and Process Intelligence
Connect process, quality and maintenance data around the actual process. Detect loss, variation and risk, then route the action that closes it.
- Manufacturing and process intelligence
- Platform
- Manufacturing / Plant Operations
- Built for
- 6 segments
- Industry coverage
- Configured to your IT and security requirements
- Deployment
The platform
Connect process, quality and maintenance data around the actual process. Detect loss, variation and risk, then route the action that closes it.
CoreGrit is the process and manufacturing execution layer. It reads what your plant already produces — control-system tags, batch records, quality results and downtime logs — and turns that stream into SPC-driven intelligence with operational context attached. Scrap, yield and process stability stop being month-end numbers and become signals your teams can act on inside the shift.
Where it applies
Built for
Manufacturing / Plant Operations
- Scrap reduction
- Yield improvement
- SPC-driven intelligence
- Process stability
The problem
Where plant value leaks
Process instability
Parameters drift inside spec long before they breach it. Without statistical context, the first visible sign is a failed batch rather than the trend that produced it.
Quality deviations
Deviations get detected at inspection, when the material is already made. The cost is fixed by then; only the paperwork remains.
Production losses
Yield lost in small daily increments never shows up as an event — it shows up as a gap between what the line should have produced and what it did.
Downtime visibility gaps
Stoppage reasons live in operator notebooks and separate logs, so the same failure repeats without ever being counted properly.
Reactive troubleshooting
Teams spend the shift explaining what already went wrong instead of acting on what is about to.
The capability
What CoreGrit puts in their hands
SPC-driven analytics
Control limits, capability and drift detection computed continuously on live process data — with the operational context around each signal.
Advanced process control (APC)
Setpoint guidance that keeps the process inside its stable operating window instead of correcting after the excursion.
Predictive process visibility
Early warning on the conditions that precede a deviation, so intervention happens while it is still cheap.
OEE intelligence
Availability, performance and quality reconciled from the same source, so the number survives scrutiny in the review meeting.
Batch quality insights
Batch-level genealogy and quality correlation — which conditions produced which result, traceable end to end.
AI-assisted recommendations
Ranked, explainable next actions for the operator and the process engineer. Outcomes, not another dashboard.
Connect → Contextualise → Detect → Decide → Improve
- ConnectSCADA, PLC/DCS, MES, ERP, QA and IoT sources — read as they are, no re-platforming.
- ContextualizeTags become process states, batches and shifts with product, recipe and asset context attached.
- CorrelateProcess, quality and downtime signals are related across lines and time, not analysed in isolation.
- Intelligently actRanked recommendations reach the operator, the engineer and the plant review with the reasoning attached.
Inside COREGRIT
Four capability areas, deployed together or one at a time
Start with the module that covers your biggest gap and extend across the layer as the pilot proves out.
Process Intelligence
The live picture of process state across lines, assets and shifts.
SPC Analytics
Statistical process control on real-time data — limits, capability, drift, and the context around each alarm.
Predictive Recommendations
Early warnings and ranked next actions before a deviation becomes scrap.
Operational Visibility
OEE, downtime and loss accounting reconciled into one operational view.
- Source data
- Process context
- KPI / deviation
- Evidence
- Owner / action
- Outcome
- Scope
- Manufacturing / Plant Operations
- Modules
- Process Intelligence · SPC Analytics · Predictive Recommendations · Operational Visibility
One environment across manufacturing and process intelligence.
Before you ask
Common questions
Anything else is a good use of the 30-minute operational diagnostic.
Do we have to replace our existing systems?
No. ProcessGrit works above the systems you already use — SCADA, PLC/DCS, MES, ERP, QMS/LIMS, maintenance, IoT and scheduling systems stay where they are. It adds the context, calculation and workflow layer between them and the operating decision.
How quickly does a deployment go live?
Diagnose — define the pain point, baseline and available data. Configure/Pilot — configure the process, KPIs, views and workflow. Validate/Deploy — validate with users and deploy the agreed scope. Improve/Scale — review outcomes and extend to more lines, sites or use cases. Each stage has an owner, an output and an exit criterion rather than a fixed duration.
How much of our team's time does it take?
Two to four hours per week from your team during the pilot. No data scientists are required — adoption support includes playbooks, training and change management.
What data does CoreGrit need to start?
Whatever the plant already generates: control-system tags, MES or batch records, QA results and downtime logs. The assessment phase confirms what is available before any deployment work begins.
What are hidden operational losses costing you?
Start with one process, one problem and the data already available. We will help map the decision gaps and the value case.
- 5 minUnderstand your process and the systems around it
- 10 minIdentify the decision gap that costs the most
- 10 minMap how ProcessGrit would close it
- 5 minAgree a focused starting point