Aetsoft Eye:
AI visual inspection
AI visual inspection software brings your operations under control. It watches every unit in real time to flag issues before they escalate. Understand what’s really happening across your production with Aetsoft Eye.
Why Aetsoft
Eye
People are not built for noticing small details – we’re not robots, after all. Rely on Aetsoft Eye, your manufacturing co-pilot that never blinks.
Bring production under full control
Inspect every unit to drastically reduce defects
While people only inspect samples, Aetsoft Eye analyzes the entire production. McKinsey reports AI-based visual inspection can improve defect detection by 90%.
Find the root cause of defects
A failed unit is only a symptom. That’s why Aetsoft Eye looks for patterns that would be invisible in human inspection.
Cut down the cost of quality
Fewer defects means cheaper production. World Economic Forum reported 52% defect reduction and 21% lower unit manufacturing costs after implementing AI machine vision.
Comply with all the standards automatically
Compliance should not depend on manual paperwork. Automatically generate timestamped visual records tied to production events to stay audit ready at all times.
How it works
Get the model trained with your cameras and launch in weeks
Aetsoft Eye:
It’s easy to start
Fine tune your AI model and launch in 2-3 weeks
AI-powered visual inspection company
Automated visual inspection
for high-stakes production
Run a smarter, tighter production line with AI visual inspection.
Use cases
001
Pharma
Automated inspection for regulated production environments.
- Verify fill levels, caps, and seals.
- Detect cosmetic and particulate defects.
- Check labels, codes, and serialization.
- Generate audit-ready visual records.
Use cases
002
Automotive
Real-time quality control across complex assemblies.
- Detect surface and paint defects.
- Identify missing or misaligned components.
- Verify assembly steps.
- Reduce recalls and rework.
Use cases
003
Electronics
High-speed inspection for precision manufacturing.
- Detect soldering and PCB defects.
- Check component placement and polarity.
- Identify micro-cracks and misalignments.
- Protect yield at scale.
Use cases
004
Consumer goods
Scalable inspection for high-volume production.
- Verify packaging integrity.
- Check labels and print quality.
- Detect cosmetic product defects.
- Protect brand consistency.
Use cases
005
Oil & gas
Vision-based monitoring for harsh and safety-critical environments.
- Detect leaks, corrosion, and surface damage.
- Monitor gauges and control panels remotely.
- Identify equipment wear and anomalies.
- Improve safety and compliance reporting.
AI models
A library of independent AI models, designed to work together or separately across your production environment.
Dedicated AI models trained for each use case
Schedule a technical consultation to assess quality improvement potential
“AI is only valuable when
it delivers measurable
outcomes.”
Pavel Sivayeu 
CTO, Aetsoft Inc
Built for zero-failure
environments
Enterprise-grade visual inspection software.
Built for advanced manufacturing
From biotech labs to heavy industrial sites, the platform adapts to complex, compliance-driven operations.
Ready for US & EU standards
Supports the most strict workflows: FDA, ISO, and other international quality frameworks.
Industrial-grade architecture
Engineered for continuous operation with edge computing. One master server monitors all distributed edge nodes.iven operations.
Why Aetsoft?
Adopt Aetsoft Eye and gain a long-term tech partner. We deliver the platform and the engineering capability to extend it across your production.
Launch AI vision inspection with confidence
Legacy integration
Powered by deep learning and computer vision
Powered by deep learning and computer vision
30% less CO2
Due to optimized processes
WeForum
40% more productive
Manufacturers become due to AI and advanced analytics
WeForum
49% less defects in just four months
Computer vision quickly reduces defects
McKinsey
Frequently asked questions
about about AI visual inspection
-
What is visual inspection?
Visual inspection is the process of checking products or components for defects, damage, or deviations from specification.
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How does AI-based visual inspection differ from traditional systems?
AI visual inspection automates this process, using software to detect issues in real time and ensure products meet defined quality standards.
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Which industries benefit most from AI inspection?
Industries with strict quality requirements, complex production processes, or high cost of defects see the greatest impact. This includes pharma, automotive, electronics, consumer goods, and oil & gas.
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How is this different from traditional vision systems?
Most legacy vision systems rely on rule-based logic and fixed thresholds. Our AI-based visual inspection approach correlates video with contextual production data, reducing false positives and improving detection stability. It focuses not only on isolated defects but also on underlying process deviations.
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Is this an AI visual inspection system for quality control or just defect detection?
It is a full AI visual inspection system for quality control. Beyond spotting defects, it provides traceability, anomaly logging, trend analysis, and structured reporting. This enables proactive quality management rather than reactive sorting.
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How long does deployment take?
Typical deployments of our AI visual inspection software go live within 2–3 weeks. The timeline depends on line complexity, data availability, and integration scope, but the rollout is structured to minimize production disruption.
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Does it replace human inspectors?
No. AI-based visual inspection systems augment human teams. The platform handles continuous monitoring and high-volume inspection tasks, while operators focus on decision-making, process improvement, and root-cause analysis.
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Can it integrate with our MES, ERP, or other production systems?
Yes. Our AI visual inspection solutions are designed to integrate with MES, ERP, SCADA, and quality management systems. Inspection results, alerts, and analytics can feed directly into your existing workflows.
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What types of defects can the system detect?
Depending on configuration, the platform can detect:
- Surface defects
- Assembly errors
- Missing components
- Labeling and packaging issues
- Measurement deviations
- Process anomalies
As an AI-powered visual inspection company, we configure detection models according to your production tolerances and risk profile.
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How does the system handle false positives?
Models are trained on your production data and calibrated to acceptable tolerance levels. By correlating multiple data sources and refining thresholds over time, the system distinguishes normal process variation from true defects more reliably.
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Is it suitable for regulated industries?
Yes. The platform generates timestamped inspection records, visual evidence, and structured logs that support audit readiness and compliance documentation. It is suitable for regulated environments such as biopharma, medical devices, and advanced manufacturing.
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Can it operate on the edge or does it require cloud processing?
Both models are supported. You can deploy fully on-premise, at the edge, in the cloud, or in a hybrid architecture depending on your security and infrastructure requirements.
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How much training data is required?
We typically start with existing production footage and operational data. Initial performance is achieved quickly, with accuracy improving as additional labeled examples are incorporated.
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How accurate is AI based visual inspection?
Accuracy depends on the specific use case and environment. During deployment, detection thresholds are tuned to balance sensitivity and false-positive rates according to your operational priorities.
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Does the system work in low-light or harsh environments?
Performance depends on camera configuration and environmental conditions. The artificial intelligence visual inspection is hardware-agnostic and can work with existing cameras or upgraded equipment. During deployment, we assess lighting and environmental factors to ensure stable detection.
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What happens after anomalies are detected?
Alerts can trigger operator notifications, automated line responses, or workflow actions. All events are logged for reporting, analytics, and root-cause investigation.
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Can it scale across multiple production sites?
Yes. Models, inspection logic, and quality standards can be deployed across lines and facilities, ensuring consistent inspection criteria and centralized visibility across operations.
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What happens if production conditions change?
Models can be retrained or adjusted to accommodate new SKUs, packaging formats, environmental shifts, or process modifications without redesigning the system from scratch.
