Novo Nordisk Uses ML for Computer Vision to Optimize Pharmaceutical Manufacturing on AWS
Novo Nordisk A/S uses computer vision and machine learning on AWS to automate manufacturing quality tasks such as cartridge counting and anomaly detection for agar plates. The company built a prototyping solution to train, deploy, monitor, and manage ML models for edge devices and to support regulated pharmaceutical operations.
- Organization
- Novo Nordisk
- Industry
- Pharma
- Location
- Denmark
- Published
- May 2026
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Novo Nordisk
- Provider
- AWS
- Maturity
- Production
- Linked source
- AWS Customer Stories
Packaged and deployed models with Amazon SageMaker Edge and Amazon SageMaker Edge Manager
Primary read
Use case focus
Showing 3 of 4
- 1Computer Vision
- 2Machine Learning Operations
- 3Quality Inspection
- Built an automated ML pipeline on AWS using Amazon SageMaker Pipelines and Amazon S3.
- Packaged and deployed models with Amazon SageMaker Edge and Amazon SageMaker Edge Manager.
- Used AWS IoT Greengrass for edge deployment and Amazon QuickSight for monitoring and anomaly review.
Architecture
Novo Nordisk built an automated ML pipeline on AWS to process images, train and tune models, evaluate results, register models, compile them for edge deployment, and monitor production inference. The workflow uses Amazon SageMaker Pipelines, Amazon S3, Amazon SageMaker Edge, Amazon SageMaker Edge Manager, AWS IoT Greengrass, and Amazon QuickSight.
Sources & evidence1
- Customer explicitly identified
- Deployment status explicitly supported
- Primary source available
- Technical implementation details available
AI-generated summary. Verify important details with the linked sources before relying on this case.
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