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Solutions
Solutions overviewPrivate AI infrastructureExisting AI optimization
Main specializations
Computer VisionSmart CityLIMSIndustrial IoT
IndustriesCase StudiesAbout usBlogContact
ENPL
GAIAA, Intelligence, engineered

Your signals, systems and constraints become the starting point for AI that can work in the real world.

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GAIAA sp. z o.o. sp.k.
ul. Sofoklesa 17
60-461 Poznaล„, Poland
NIP: 7811993317
KRS: 0000777888
ยฉ 2026 GAIAAPrivacy policyhello@gaiaa.eu+48 666 308 008LinkedIn
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Case study: Manufacturing

When workforce time needs the same precision as production.

Worker presence, machine activity and project budgets became one governed, automated record.

SystemOutcomesRelated workDiscuss your case

System

The project and the problem

A global medical-device and eye-care manufacturer needed to replace manual work-time logs with objective evidence of where floor workers were working and which active production job their time should support. Separate location, machine and payroll systems could not reliably connect physical presence to the correct project budget.

How the process worked

GAIAA connected an Omlox-compatible UWB real-time location system to the MES through an on-premise integration layer. The software validates an operator's position against active machine and work-order state, then sends the resulting, audit-ready allocation to payroll and reporting tools.

Location-to-allocation flow

See how location, machine state and payroll allocation connect.

Use the controls below to inspect the key stages, constraints and validation decisions in that process.

Control view

Validated workforce allocation

Choose a work area to inspect how the physical event becomes a governed allocation.

Production floor
UWB location event, 10 cm precision
RTLSOperator present at Cell A

Presence validated inside the machine geofence.

MESMachine A ยท Active

Active work order is the active work order.

PayrollAllocate to the mapped project budget

Validated labor time is routed for reporting.

Outcomes

Operating constraints

  1. 10 cm positioning accuracy around dense machinery
  2. Location and machine state must agree
  3. Sensitive workforce data remains on-premise
  4. Existing MES and payroll systems stay in place

What changed?

  1. Automated time and attendance evidence
  2. Granular, machine-linked job costing
  3. Project budgets charged from validated activity
  4. Real-time administrative visibility

Evidence retained: Each allocation keeps the RTLS position event, MES machine state, work order and resulting payroll route together for review.

Related work

SolutionIndustrial IoTSolutionPrivate AI infrastructure

Discuss your case

Have a similar operating problem? Share the environment, constraint and result you need. We can discuss the engineering path without exposing confidential details.

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