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Manvis
See Everything. Miss Nothing.
The AI vision system that turns every camera in your plant into an intelligent observer — detecting defects, verifying processes, measuring work, and monitoring safety. Continuously, 24/7, with no fatigue and no blind spots.
The Cost of the Detection Gap
Your inspectors catch 80-85% on a good shift. That 15-20% miss rate at 400 parts/hour means defects reach your customers. Manufacturers spend 20% of revenue on cost of poor quality — and every defect that escapes costs 8-12x what it costs to catch in-plant. IE time studies take 2-5 days per workstation; most plants complete less than 20% of planned studies per year (IIE). The processes that need documentation most are the ones that change fastest — and your IE team is perpetually behind. Human inspection accuracy drops from 85% to 60-70% under fatigue (MIT Human Factors). That is not a training problem. That is a biological limitation applied to an industrial requirement. 80% of the cost of poor quality goes to failure and appraisal, not prevention. The economics are inverted — and they stay inverted as long as detection depends on human consistency.
What We See on the Floor
At 400 parts/hour, a 15% miss rate means 60 defective parts per hour reach the next station — or your customer. That is not a quality problem. That is a detection system problem. Your Cpk and process capability metrics tell you the process is capable, but the measurement system — human visual inspection — cannot keep pace. An MSA (measurement system analysis) on manual inspection would fail repeatability and reproducibility criteria in most plants. Most plants have cameras already. They record footage nobody watches. Manvis does not require new hardware — it makes your existing cameras intelligent. The infrastructure investment is already made. The intelligence layer is what is missing. Your IE team is 6 months behind on time studies. Every new hire adds to the backlog. The processes that need documentation most are the ones that change fastest. SOPs exist for some stations but not others. Safety violations are caught after the incident, not before. The FMEA lists prevention controls that are not actually in place — because the detection system those controls depend on is manual and inconsistent.
What Changes With
Manvis
Before Manvis
Human inspectors catch 80-85% on a good shift
Inspection accuracy drops with fatigue
Defect data lives in paper logs
SOP verification requires an auditor walking the floor
Time studies take days or weeks per workstation
SOP documentation takes weeks per process
5S scoring done by clipboard audit
Safety violations caught retroactively
After Manvis
AI catches 99%+ on every shift, every hour — OEE quality component improves directly
No fatigue, no shift variation — same performance at 6 PM as at 6 AM
Defect data classified, trended, and surfaced as actionable intelligence
Process compliance monitored continuously — deviations flagged in real time
Video-based time studies completed in hours
SOPs generated from production video
AI scores 5S compliance continuously from existing cameras
PPE and zone violations detected in real time — before the incident
Five Pillars. Complete Plant Intelligence.
The Numbers
defect detection accuracy — every shift, every hour, no fatigue
reduction in quality escape rate with 100% inspection coverage
faster time studies than manual IE methods
reduction in safety violations through continuous monitoring
Supporting industry data:
$1.7 trillion — global annual cost of quality failures in manufacturing (ASQ/NIST)
Manufacturers spend 20% of revenue on cost of poor quality (ASQ)
Human inspection accuracy: 80-85% ideal; 60-70% under fatigue (MIT Human Factors)
-E time studies: 2-5 days per workstation; most plants complete <20% of planned studies/year (IIE)
The Business Case
The ROI Model
Track A (Video Upload):
IE time studies currently take 2-5 days per workstation. Manvis completes them in hours. For an IE team spending 40% of capacity on studies, the productivity recovery alone justifies the subscription. Your IE team shifts from data collection to process improvement — the work they were hired to do.
Track B (CCTV):
You run N inspectors per shift at $55K each. Manvis replaces the detection function — not the inspector — at a fraction of that cost. Add quality escape prevention (every escape costs 8-12x the in-plant catch cost) and the payback is measured in weeks. The OEE quality component improves, Cpk data becomes continuous instead of sampled, and your FMEA prevention controls gain the detection backbone they require.
Built for the Teams That Own Quality, Safety, and Productivity
1
Quality Managers
Your inspectors catch 80-85%. Manvis catches 99%+ in early deployments. Every shift, every hour. You know exactly what left your plant — and if something escaped, you know where, when, and why. MSA compliance improves because the measurement system is consistent.
2
IE Managers
Stop spending weeks on time studies. Manvis completes them from video in hours — VA/NVA analysis across all workstations. SOPs generated automatically. Your backlog clears in weeks, not years.
3
Safety / EHS Managers
You cannot be everywhere. Manvis can. PPE compliance, zone monitoring, and ergonomic alerts — in real time, from existing cameras.
4
Plant Managers
Replace the cost of manual inspection with AI coverage. Reduce quality escapes, improve safety compliance, and get audit-ready documentation produced automatically.
Purpose-Built for Manufacturing
Part of the SME-Empowerment Platform
Manvis is the sensing layer of the SENSE → PLAN → EXECUTE platform:
Manvis is powerful alone. Connected to the platform, every detection becomes an action, every observation becomes intelligence, and the loop never stops closing.
Why Manvis, Not Traditional Vision Hardware
Traditional Vision (Cognex, Keyence)
Programmed for one defect type per deployment
Quality inspection only
Hardware-dependent, per-station installation
No integration with corrective action systems
Static rules, manual programming for changes
No connection to planning or execution
No contribution to OEE or Cpk analytics
Manvis
Learns from your specific products and adapts
Quality + process + safety + compliance + time studies
Works with existing camera infrastructure
Defects flow directly into EmpowerOps CAPA workflows
Deep learning models retrain as your products evolve
Time study data feeds Asireon; detections feed EmpowerOps
Continuous quality data feeds OEE quality component and process capability metrics
Common Questions
We already have Cognex / Keyence.
Our inspectors are experienced — we trust them.
We don't have camera infrastructure.
The cameras feel like surveillance.
See Manvis in Action
Book a consultation. We will walk through the five pillars in the context of your plant — your quality challenges, your inspection process, your camera infrastructure, your use cases.
