Industries/Manufacturing
Industries · Manufacturing

AI for the plant floor — not just the front office.

We help manufacturers cut unplanned downtime, catch defects earlier and plan production with confidence, starting with the machine and MES data you already have.

LINE 2 · LIVE Illustrative Defect 0.97 Vision inspection Press 07 Vibration rising Predicted failure Press 07 Bearing · in ~[X] days Schedule repair Production schedule Re-planned around repair Data sources PLC ✓MES ✓ERP ✓CMMS ✓
The challenge

Your plant generates data every second. Most of it goes unused.

PLCs, MES, quality logs and maintenance records sit in separate systems with different formats. Before AI can predict a failure or plan a line, that data has to be captured, cleaned and connected. That foundation is where we start.

Where AI helps

Four places AI pays off on the plant floor.

01

Predictive maintenance

Spot failing motors, pumps, presses and spindles from vibration, temperature and current data, and schedule repairs before they stop the line.

Built with Industrial IoT & Edge →
02

Visual quality inspection

Cameras and vision models flag scratches, misalignments and missing parts at line speed, so defects are caught before they ship.

Built with Data & AI Products →
03

Production scheduling

Plan work orders around machine availability, materials and due dates, and re-plan quickly when a machine goes down or an order changes.

Built with LogiTrac360 →
04

PLC and MES data readiness

Capture, clean and connect controller, MES and historian data, so it is ready for dashboards, analytics and AI models.

Built with AI Integration & Automation →
Systems we work with

We connect to what your plant already runs.

PLCs and SCADAMESHistoriansERPCMMS and maintenance systemsQuality systemsVision cameras

Which line costs you most when it stops?

We’ll scope a focused pilot around it, from data to prediction.

Find your best AI use cases →
LET'S TALK

Start with an AI readiness conversation.

Tell us what you'd like AI to change in your business. We'll come back with an honest view of where to start — and where not to.

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