STRATUSGRID

Automated Quality Control

StratusGrid and AWS teams are working together to improve the cloud experience, including automating quality control in product manufacturing pipelines or detecting anomalies in the energy/utilities industry. Our Solutions Architecture team built a solution using Amazon Lookout for Vision and created technical training resources.

5 Stars Automated Quality Control
Automated Quality Control

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StratusGrid Services

StratusGrid engineers can deliver projects that utilize the core computer vision capabilities in AWS, and build integrations surrounding it. Integrations that may be useful to customers in this space include:

Notification / alerting mechanism of newly identified anomalies

Notification / alerting mechanism of newly identified anomalies

Extracting and processing individual frames from video

Extracting and processing individual frames from video

Long-term storage of analysis in databases, for auditing

Long-term storage of analysis in databases, for auditing

Using drone fleets for automated data collection

Using drone fleets for automated data collection

Gathering and resampling images and video for long-term archival

Gathering and resampling images and video for long-term archival

Our Approach to Computer Vision

StratusGrid builds off of cloud services provided by partners such as Amazon Web Services (AWS), and either integrates with them as-is or customizes them to specific customer use cases. We can develop computer vision integrations that utilize object detection and anomaly detection.

Problem Analysis

Problem Analysis

We start by assessing your end-to-end business model, and then identify opportunities to automate and improve quality controls, using machine learning models designed for computer vision tasks.

Model Training

Model Training

If model fine-tuning / training is required, identify the data required to train a custom model version, and develop a data quality and validation pipeline. Then, we train a custom model and deploy it for production inferencing.

Integrate

Integrate

We develop custom integrations, using cloud native services, leveraging computer vision, storage, analytics, and alert management tools, based around industry leading toolchains.

Why Automate Quality Controls With Computer Vision?

Accuracy

Accuracy

Computer vision can accurately detect important real-life events, such as anomalies in manufacturing pipelines, defects in above-ground energy transmission lines, and related equipment.

Automation & Scale

Automation & Scale

By automating anomaly and object detection tasks with cloud services, you can scale your business operations virtually infinitely. Automated computer vision scales more efficiently than hiring additional dedicated labor for quality control purposes.

Extensibility

Extensibility

Machine learning models built for computer vision are customizable, and can be adapted to your specific use cases.

How We Do It

Automated Quality Control: How we do it.

Containers

Deploy long-running services, using an industry standard, cross-cloud application packaging format.

Serverless

Develop small functions (microservices) to fulfill and scale individual components of the overall computer vision solution.

Amazon Rekognition

Fully managed service that provides APIs for object detection and image classification, and training on custom labels.

Amazon Lookout for Vision

Fully managed computer vision service for anomaly detection, supporting training on custom datasets.

Amazon DynamoDB

Store semi-structured results from computer vision tasks, in a high performance key-value store.

AWS Step Functions

Orchestrate data ingestion, transformation, detection, and results storage.

Quotes

With a deep understanding of FinOps, the Stratusgrid team have developed a unique application that provides insightful analysis to help drive cloud cost efficiencies and spot opportunities for architectural improvements. The team’s balanced understanding of SaaS business and technology drivers is a real differentiator."

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