Defects are found at final inspection, or by the customer.
What it costsScrap, rework and returns.
What changesCameras and models inspect every part on the line, and flag defects as they happen.
Agentic OS · SignalAI Transformation · Industrial AI and IoT
AI on the factory floor, the fleet and the site.
Cameras, sensors and machines already produce the data. We turn it into decisions: defects caught on the line, safety risks flagged on site, failures predicted before they happen, and assets tracked across the fleet, connected to your ERP and maintenance systems.
Six uses, one data flow
- InspectVisual quality inspection
- ProtectSite safety and PPE
- TrackFleet, cold chain, equipment
- PredictMaintenance before failure
- BuildingsEnergy and BMS analytics
- Shop floorOEE and traceability
Edge and cloud, connected to ERP and maintenance systems
Written for
COOs, plant heads, quality and maintenance leaders, and fleet and facilities managers
The question you came with
How do we use the data our machines, cameras and vehicles already produce?
Part of Enterprise AI Transformation
Where AI meets physical operations. Detections from cameras, sensors and vehicles become actions in your ERP and maintenance systems, with the same audit trail.
See the whole programmeWhat your operations are missing
If two of these are true, the rest of this page is about you.
Machines fail without warning.
What it costsUnplanned downtime and rushed repairs.
What changesSensor data and models predict failures, and create maintenance work orders in time.
Agentic OS · AgentsNobody knows where assets are.
What it costsLost equipment, idle vehicles and cold-chain breaks.
What changesTelematics and tracking for fleet, equipment and cold chain, with alerts on exceptions.
Agentic OS · FlowShop-floor data stays on paper.
What it costsOEE is a guess, and traceability takes days.
What changesMachines and stations connected, with OEE and traceability reported live.
Agentic OS · PulseHow a signal becomes an action
The same flow for a camera, a sensor or a vehicle.
- Step 01 · Capture
Cameras, sensors and machines
Data collected at the edge, filtered and sent securely, even over weak connections.
- Step 02 · Detect
Models find what matters
Vision and ML models spot defects, risks and early signs of failure.
- Step 03 · Act
Work orders and alerts
The right person is alerted, and a work order, hold or reorder is created in your systems.
- Step 04 · Improve
Models and processes tuned
Results reviewed, false alarms reduced, and the process improved from what the data shows.
What we build
The capability on the left, what your team would notice on the right.
- Quality
Visual quality inspection
Computer vision models trained on your parts and defects, running at line speed.
- Safety
Site safety, PPE and progress monitoring
Cameras flag missing PPE, unsafe zones and progress against plan on construction and plant sites.
- Tracking
Telematics and asset tracking
Fleet, cold chain and equipment tracked, with temperature, location and usage alerts.
- Maintenance
Predictive maintenance
Sensor data and machine learning predict failures and raise work orders in your maintenance system.
- Buildings
Smart building and energy monitoring
BMS integration and metering analytics to cut energy use and spot faults.
- Shop floor
Digitisation, MES and digital twins
OEE, traceability and digital twins linking BIM, GIS and live operating data.
What stays yours
We build and hand over
- Models, training data and evaluation results
- Edge and cloud configuration
- Dashboards, runbooks and training
You keep and control
- Your devices, data and networks
- Your ERP and maintenance systems
- Admin access, in your name
How an engagement runs
The same four steps whatever we build. The first one is small, fixed-fee and useful on its own.
Start with a fixed-scope offer
A fixed scope, a set timeline and a deliverable you keep. The quickest way to start.
Pilot
Visual Quality Inspection Pilot
A vision model inspecting one line, measured against your inspectors
- Time
- 8 to 10 weeks
- Price
- Fixed fee, agreed on a call
- For
- Plant heads, quality managers and operations leaders
The problem. Defects slip through manual inspection, and are found late as scrap, rework or customer returns.
What happens, week by week
- Weeks 1 to 2Choose the line and defects
Pick one line, agree the defect types and acceptance criteria, and check cameras and lighting.
- Weeks 3 to 5Collect and train
Images captured and labelled with your quality team, and the model trained on your parts.
- Weeks 6 to 8Run in shadow mode
The model inspects alongside your inspectors, and results are compared part by part.
- Weeks 9 to 10Decide on rollout
Accuracy, speed and savings reported, with a plan and cost for more lines.
You get
- A trained inspection model for one line
- Shadow-mode results against your inspectors
- Integration with line alerts or MES
- Rollout plan and cost
Who signs off
Plant head and quality manager
What we need from you
Line access, sample parts, and a quality lead to help label defects
Not sure where to start? Begin with the AI Transformation Review: two to three weeks, $1,500, credited to month one.
Questions
Do we need new cameras or sensors?
Often not. We start with the cameras, PLCs and sensors you have, and add hardware only where the data is missing.
Does it run on the edge or in the cloud?
Both. Time-critical detection runs at the edge, and training, reporting and history run in the cloud.
How accurate is visual inspection?
It depends on your parts, lighting and defect types. The pilot measures it on your line against your inspectors before any rollout.
How does this connect to AI Transformation?
Detections become actions in your ERP and maintenance systems, under the same controls and audit trail as every other agent.
Keep going
Where Industrial AI and IoT fits your industry, what to read next, and the tools involved.
Industries we do this in
Tools we review for this
AI transformation for the agentic engine era
Start with a fixed-fee AI transformation review. We map your systems, data and teams against the six layers of Pegasus Agentic OS and name the first workflows to hand to agents. You keep the findings whether or not you work with us.