Most computer vision projects produce impressive demos and unreliable production systems. Agmis offers computer vision consulting that builds vision-based AI running accurately on your actual hardware, against your actual products, in the conditions your facility operates in - not in a controlled lab.
Book a Strategy CallThe gap between a computer vision prototype and a production system is wider than most vendors admit. Lighting changes. Product variants multiply. Cameras shift. And the model that scored 97% on your test dataset starts missing defects on your production line within three months. Working with the right computer vision consulting team means addressing these realities from the start.
That's the gap Agmis fills. We design computer vision systems for real operating conditions from day one - variable lighting, high throughput, hardware constraints, and the full range of your product catalogue - not just the clean examples in your sample dataset.
Off-the-shelf vision models are trained on general-purpose image data. Your defects, your products, your facility - these require models trained specifically on your operating conditions. We don't adapt generic solutions. We build custom ones.
Our automotive seat inspection system runs at 2.2 seconds per unit - 27x faster than the manual process it replaced, at 99% accuracy across 40+ seat variants. That's the throughput standard we build to.
ISO/IEC 27001 certified. EU-based. We understand the data handling requirements for healthcare imaging, food production, and industrial manufacturing - sectors where compliance isn't optional.
Our computer vision consulting delivers across five application areas, each with production deployments and measurable results behind it.
We build automated inspection systems that detect defects, surface irregularities, dimensional deviations, and assembly errors at production speed. Our systems cover textiles, food products, automotive components, pharmaceutical packaging, and engineered materials - trained on your specific defect taxonomy and production tolerances.
We deploy continuous monitoring systems that track PPE compliance, detect hazardous conditions, and flag safety violations in real time. Our food manufacturing deployment achieves 93% accuracy on hardhat and vest detection and 100% on face mask detection - running across live production shifts, not spot checks.
We build computer vision systems for medical imaging workflows - CT scan processing, pre-surgical planning, anatomical segmentation, and diagnostic support tools. Our Ortho Baltic deployment reduced CT scan processing time from 3 hours to 60 seconds, enabling same-day surgical planning that was previously impossible.
We design detection and tracking systems for retail queue monitoring, inventory visibility, vehicle counting, and crowd analysis. Our retail queue management system reduced cashier idle time by 57.66%, prevented 237 queue incidents, and saved 2.5 hours per store daily.
We apply computer vision to crop health monitoring, yield estimation, harvest quality grading, and environmental inspection. This includes drone-based imagery analysis, multispectral classification, and field-level decision support tools built for real agronomic workflows.
Four stages, each with a defined output - not open-ended sprints.
We assess your operating environment, hardware infrastructure, and the specific visual task you need to automate. This includes camera setup evaluation, lighting analysis, sample data review, and a realistic assessment of what accuracy is achievable in your conditions. If the problem isn't well-suited to computer vision, a responsible computer vision consulting engagement tells you at this stage.
We work with your team to collect a representative training dataset - covering your full product range, defect types, and operating conditions. Where labelled examples are limited, we apply data augmentation and synthetic generation techniques. We train custom models on your data, not fine-tuned versions of generic architectures.
We integrate the vision system into your existing infrastructure - connecting to your cameras, conveyor systems, PLCs, and production management software without requiring a full hardware overhaul in most cases. We build deployment pipelines designed for your environment: edge, cloud, or on-premise.
We configure performance monitoring, set drift detection thresholds, and run a structured knowledge transfer with your team. As your product range changes, we handle model updates. You own the system after we leave - we make sure your team can maintain and develop it independently.
Numbers from production systems built through our computer vision consulting - not controlled test environments.
Leading European Manufacturer
99% detection accuracy across 40+ seat variants. 2.2 seconds per unit. Deployed on a live production line.
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Ortho Baltic
Pre-surgical CT scan processing reduced from 3 hours to 60 seconds. Enables same-day surgical planning that was previously impossible.
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Mantinga Food Manufacturing
93% accuracy on hardhat and safety vest detection. Deployed across a live production facility with continuous shift monitoring.
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AI Power Grid Inspection for ESO
Average precision across all power grid infrastructure elements - insulators, crossarms, pillars, and poles - analyzed from 200,000 inspection photos
Read the case studyWe don't position ourselves as a horizontal computer vision vendor. Our computer vision consulting deployments are concentrated in the sectors below - where we've built real engineering depth over multiple projects.
Defect detection, surface inspection, dimensional verification, assembly validation, production scheduling
Medical imaging analysis, pre-surgical planning, anatomical segmentation, diagnostic support
PPE compliance monitoring, crop quality grading, yield estimation, contamination detection
Queue management, shelf analytics, inventory monitoring, customer flow analysis
Aerial structural inspection, power line monitoring, infrastructure assessment from drone imagery
Perimeter monitoring, intrusion detection, anomaly detection, critical infrastructure protection
Commercial vision platforms are built around general-purpose tasks and standard defect categories. Your production environment - your lighting, your products, your defect types - requires models trained on your specific data. Platform accuracy on generic benchmarks doesn't translate to your production line. That's where custom computer vision consulting delivers what platforms can't.
In most cases, we integrate with your existing camera setup. We'll assess your current hardware during the technical audit and tell you clearly if anything needs upgrading - and why - before any development begins. We don't require proprietary hardware or preferred vendors.
It depends on the complexity of the task. For simpler inspection tasks with clear defect categories, a few hundred labelled examples per class can be sufficient. For more complex tasks - fine-grained defect classification, medical imaging - we need more. We assess your data during the audit phase and can supplement with synthetic data generation where needed.
We configure drift monitoring as part of every deployment. When accuracy drops below a defined threshold, we have a process for collecting new examples and retraining. We document this process fully during handover so your team can execute it independently, or we can handle it under a retainer arrangement if you prefer.
Audit and scoping: 2-3 weeks. Data collection and model training: 4-10 weeks depending on data availability and task complexity. Integration and deployment: 4-8 weeks. Total timeline for a focused single-task system typically runs 3-5 months from first conversation to live production. More complex multi-task deployments take longer - we scope timelines in the audit phase.
Yes. Agmis is ISO/IEC 27001 certified and operates under EU data protection frameworks. We have experience with air-gapped deployments and data handling requirements for healthcare and pharmaceutical clients. Our Ortho Baltic engagement is an example of a clinical computer vision consulting deployment that required careful handling of patient imaging data.
