For operations with production data

Production data, finally steering the operation.

You have dashboards. The question is whether anyone is acting on them. We build the foundation and the Activate layer that turn production, planning and quality into actual operational decisions.

app.powerbi.com · Production Performance LIVE DEMO · SAMPLE DATA MeadowField Foods Production Performance · Plant Cockpit Site: Son Line: All Shift: Current LAST REFRESH 14:20 OEE TODAY78.0%▼ -2.1pp vs 30d avg OUTPUT VS TARGET84%23.4k / 27.8k units DOWNTIME TODAY142min3 unplanned stops LINES RUNNING6/71 in changeover FIRST-PASS QUALITY97.4%▲ +0.3pp vs week Active downtime & deviations — needs attention now DT-1147 Filler dose drift 1h 22m Line 4 · Filler 200 · running at 86% of rate ACTION → Check dose calibration zone 2 DT-2403 Changeover overrun 47 min Line 2 · SKU switch 500ml → 1L · +22 min over standard ACTION → Confirm format parts staged before switch AI SUGGESTED FIX Restore Line 4 dose calibration Expected +3.2pp OEE on Line 4. Planner validates → OEE per line · today Target 85% 83L1 74L2 88L3 56L4 80L5 85L6 68L7 OEE trend · 30 days 30-day avg 78% today Plant OEE %

Trusted by machine builders and manufacturers.

TMI Van Loon Group Tecnical IXON
Before the dashboards

Having data isn't the same as knowing what to measure.

Your lines, your ERP and your MES already produce more numbers than anyone reads. The hard part is knowing which of them actually tell you something.

So we start with the decision, not the data: what do you want to decide, and what's worth measuring to support it. That is the first thing the Quick Scan settles.

Decision KPI Signal
Questions teams still can't answer

Which line loses the most, and why?

Where is maintenance effort spent without return?

82%OEE

Are we hitting the OEE we target?

!

Which parts will fail before the next stop?

How we work in your operation.

Four steps from production data to decisions on the floor. You decide which steps we do, and which stay with your team.

ERPMESPI
1 Connect

Connect to your existing stack

We integrate with your ERP (SAP, D365, Exact, Infor), MES, historians (PI System, AVEVA) and sensor layers. We don't replace what works. Vendor-neutral by default.

GOLDOperationally usable SILVERClean and structured BRONZERaw history
2 Foundation

Build the data layer your plant runs on

Medallion architecture on Azure: Bronze, Silver, Gold. Hosted in your tenant or ours, depending on your data residency and food-safety / traceability requirements.

PLANNEROEE78% MAINTENANCEMTBF436h OPS DIRECTOROTIF94%
3 Reporting

Build the reports each role actually uses

Power BI per role: planner sees OEE per line with downtime causes, maintenance sees MTBF, ops director sees OTIF. One foundation, distinct working views.

AIProposes Validates LEARNS FROM EVERY CHOICE
4 Activate

Move from dashboard to decision

The Activate layer proposes a root cause, a forecast adjustment, or a sparepart order with reasoning. Your planner, engineer or maintenance manager validates. Audit-trail and learning loop built in.

Full technical breakdown of every building block on what we build →

Martijn van Dijk
Who builds this for manufacturers

The data was there. The shared truth wasn't.

Across production sites, the same pattern kept showing up. The ERP team had its definitions, the MES team had others, the planners trusted their own spreadsheet, and the operations director got reports that didn't match what the floor saw. Everyone was right. Nobody was aligned.

We built StriData to close that gap for manufacturers. Not a generic BI project. One Medallion foundation that aligns ERP, MES, historian and sensor data, with an Activate layer that turns shared facts into validated decisions. Your planner and maintenance manager stay in control. Your plant starts steering on numbers everyone trusts.

Martijn van DijkFounder · StriData
1,500+
machines connected
40+
countries with deployments
30+
dashboards delivered
Customer case

What this looks like in practice.

Manufacturer · Food production

Machine data and ERP combined for real-time operational control.

Van Loon Group runs multiple food production sites. StriData linked PatchOEE machine data and Reflex ERP at production-order and line level, creating one reliable foundation for shop-floor screens and Power BI reporting across locations.

Real-time
order status on the floor, via tablets at the line
Order-level
machine output linked to production orders
One base
OTIF, forecast and staffing reports reuse it

“By connecting machine data and operational information, we gained more insight into what happens on the production floor. That helps us respond faster and make better-informed decisions.”

Jack Spierings · Van Loon Group

Read the Van Loon case

Questions manufacturers ask us.

Which source systems do you connect to?

ERP (SAP, Dynamics 365, Exact, Infor), MES and QMS systems, historians (PI System, AVEVA Wonderware), file- and API-based sources, custom databases, and direct sensor layers when needed. We work vendor-neutral and build on what is already there.

We have dashboards already but no one looks at them. What's different here?

The difference is the Activate layer. We don't stop at reports. We build the workflow where the system proposes an action with reasoning, your planner or maintenance manager validates, and the action is logged. That changes behaviour where dashboards alone don't.

How many sites do we need to make this worthwhile?

One. We typically start with a single site, validate the approach, and replicate to others once it lands. Multi-site rollouts work best when the first site has produced concrete proof.

How does the engagement work?

Quick Scan as the entry point (short, fixed-price exploration). Optionally an Architecture Scan for deeper roadmap work. Then a phased build of the foundation and first module. After go-live, an ongoing managed service with SLA, or full handover to your team.

Can you work alongside our existing BI or data team?

Yes. We frequently work as a specialist layer next to internal teams. We bring the Medallion methodology, the Activate layer, and the production-grade delivery patterns. Your team keeps ownership where they have it.

What if we already have a data warehouse?

We build on top of it rather than introducing a second layer. The Quick Scan establishes what is there, what is usable and what is missing. Many of our engagements begin exactly this way.

Ready to make your production data work harder?