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Self-serve answers from plant data.

Drag-and-drop visual queries and dashboards across MES, ERP, sensors and supplier data — built by the ops and quality teams who actually need the answers, not by IT tickets.

For

Operations ManagerQuality ManagerPlant AnalystEngineer
rockq.app/explore/scrap-by-line

Explore / New view

Scrap by line · last 30 days

Sources

Filters

PlantisPlant 1
LineinL2 · L3 · L5
Datelast30 days

Group by

Line · Day

Metric

Scrap %

Preview

0257
L2L3L5
The problem

Most plant data dies in tickets to IT.

BI projects take quarters. Ops can't wait. Self-service tools give freedom but lose governance. RockQ lets ops and quality compose visual queries across systems — with the same security model as the rest of the platform.

What's included

Capabilities included.

Self-service analytics across machine, MES and ERP data — with sharable views, alerts and a path to apps when a query graduates.

Self-service Analytics

Drag-and-drop dashboards over plant, ERP and supplier data — built by ops and quality, not by IT tickets.

Machine Data Collection

Connect to any PLC or sensor using vendor-independent standard protocols. Centralize data for analysis and reporting without vendor lock-in.

Scrap Analysis

Identify root causes of scrap. Analyze defect patterns by shift or machine to implement corrective actions.

Question gallery

Questions ops teams already have. Answered.

These are the kind of questions our customers used to wait two weeks for. Now they take ninety seconds — composed by the team that asked them.

Scrap % by line, last 30 days?

Bar · by lineauto
MES · SPClive

Throughput per shift, last week?

Bar · by shiftauto
MESlive

Energy per good part, EV-Stator-R3?

Line · dailyauto
Sensors · MESlive

Top NCR causes this quarter?

Bar · by causeauto
Qualitylive

On-time delivery by supplier, last 6m?

Bar · by supplierauto
ERP · Receivinglive

Compose

Ask the next one.

Type a question, point at sources, share the view. Same governance, no IT ticket.

Why was Line 5 slower last shift?
How it works

From question to dashboard, same hour.

1

Connect

Connect to MES, ERP, data lake, sensors and supplier feeds — with one governance model.

2

Compose

Pick sources, filters, groupings and metrics. No SQL needed — but exposed if you want it.

3

Visualize

Charts, tables, KPIs and maps. Live, refreshable, with row-level security.

4

Share

Save as view, alert on threshold, or graduate into a full no-code app on the platform.

Outcomes

Outcomes the floor feels.

<1 h

Time to first chart

Ops users go from question to live view without a ticket.

10×

Self-served questions

Compared to the BI backlog the same teams used to wait on.

<1 wk

Plant onboarded

From connector to dashboards, with governance preserved.

Connects to
SAPOracleSnowflakeDatabricksPostgresCSV / Excel
Talk to the people who built it

An expert behind every solution.

Real engineers, real factory experience. Drop them a line — they'll respond, scope and propose a working architecture, not a sales deck.

Senad Redzic

Senad Redzic

Head of AI

Most factory AI dies in PoC. Mine ships because we treat the model as one piece of a deployed system — connected to live data, owned by your team, governed end-to-end.
Stefan Höhenberger

Stefan Höhenberger

COO

Manufacturing teams own their systems again. We pick problems where the win is measurable in the first quarter, then ship from there.

Compose one view we'd kill for.

Tell us a question your team has been waiting on. We'll wire the sources and ship the view, governed and live.

Self-serve answers from plant data. | RockQ Technologies