Opsio - Cloud and AI Solutions
AI Defect Detection

Defect Detection with Deep Learning for India

Move beyond open-source demos to production-grade defect detection. Opsio takes deep learning defect detection from GitHub proof-of-concept to scalable, edge-deployed quality control systems for Indian manufacturers — with custom models, MLOps pipelines, and PLC integration.

Trusted by 100+ organisations across 6 countries

PoC to Prod

Full Journey

97%+

Accuracy

6 wk

Deployment Time

Open Source
NVIDIA Jetson
MLOps
Delivered by Opsio

What's Included

01

Model Selection & Customisation

Evaluate open-source architectures and customise with your defect data for optimal accuracy and speed.

02

Production Engineering

Model optimisation, quantisation, and TensorRT compilation for real-time inference on edge devices.

03

MLOps Pipeline

Automated training, validation, deployment, and monitoring pipelines for continuous model improvement.

04

Hardware Integration

Camera selection, lighting design, and PLC/SCADA integration for end-to-end quality control automation.

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Magnus Norman

Head of IT · Löfbergs

From GitHub Demo to Production Defect Detection

GitHub is full of impressive deep learning defect detection notebooks — YOLOv8 for object detection, ResNet for classification, U-Net for segmentation — but the gap between a notebook demo and a reliable production system is enormous. Indian manufacturers who try to deploy these models in-house often find themselves stuck with models that work in the lab but fail on the production line due to lighting variations, camera angles, class imbalance, and inference speed limitations. Opsio bridges this gap with production engineering expertise. We evaluate open-source architectures, select the best starting point for your specific defect type and production environment, then customise the model with your data, optimise for edge inference, build MLOps pipelines for continuous improvement, and integrate with your PLC/SCADA and MES systems. The result is a system that runs reliably 24/7 without data scientist intervention.

Our team has productionised defect detection systems across Indian manufacturing verticals — taking models from initial proof-of-concept to full-scale deployment in as little as 6 weeks. We handle everything from camera selection and lighting design to model training, edge deployment, and ongoing monitoring.

Model Selection & CustomisationAI Defect Detection
Production EngineeringAI Defect Detection
MLOps PipelineAI Defect Detection
Hardware IntegrationAI Defect Detection
Open SourceAI Defect Detection
NVIDIA JetsonAI Defect Detection
MLOpsAI Defect Detection
Model Selection & CustomisationAI Defect Detection
Production EngineeringAI Defect Detection
MLOps PipelineAI Defect Detection
Hardware IntegrationAI Defect Detection
Open SourceAI Defect Detection
NVIDIA JetsonAI Defect Detection
MLOpsAI Defect Detection

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Why Choose Opsio for Cloud Services

PoC to Production

We specialise in taking ML models from demonstration to reliable 24/7 production systems.

Open-Source Savvy

Deep expertise with YOLO, ResNet, EfficientNet, U-Net, and vision transformers.

India Manufacturing

Production-tested across Indian steel, auto, electronics, and pharmaceutical manufacturing.

6-Week Deployment

Rapid deployment methodology that gets you from data to production in 6 weeks.

Not sure yet? Start with a pilot.

Begin with a focused 2-week assessment. See real results before committing to a full engagement. If you proceed, the pilot cost is credited toward your project.

Our 4-Phase Delivery Process

Key Takeaways

  • Model Selection & Customisation
  • Production Engineering
  • MLOps Pipeline
  • Hardware Integration

Defect Detection with Deep Learning for India — FAQ

Can you use an open-source model we found on GitHub?

Yes. We evaluate its suitability for your use case, then customise, optimise, and productionise it with your data.

What hardware do you recommend?

NVIDIA Jetson Orin for edge deployment, with GigE Vision industrial cameras and controlled lighting setups.

How is this different from commercial inspection software?

Custom models trained on your specific defects outperform generic commercial solutions and cost less at scale.

Do you provide the training data?

We assist with data collection strategy, camera setup, and annotation. You provide production line access and sample products.

What happens when new defect types appear?

Active learning pipelines flag unknown anomalies for labelling, and models are retrained automatically.

Still have questions? Our team is ready to help.

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Editorial standards: Written by certified cloud practitioners and reviewed by our engineering team.
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Defect Detection with Deep Learning for India

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