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AWS Solutions Library

Guidance for Kelvin AI on AWS

Overview

This Guidance demonstrates how to optimize industrial operations in real-time by implementing Kelvin AI's Autonomous Control Operation tools on AWS infrastructure. Kelvin AI connects seamlessly with existing industrial systems through edge nodes that process data locally, ensuring continuous operation even during connectivity disruptions. The system combines edge computing for immediate control actions with cloud capabilities for advanced analytics, allowing industrial teams to make data-driven decisions with enterprise-grade security. You can achieve improved operational efficiency, reduced downtime, and enhanced production quality while maintaining complete control over your industrial processes.

Benefits

Enable autonomous closed-loop control at the edge while maintaining continuous operations during connectivity loss. Drive operational efficiency with minimal latency response times.

Deploy consistent Kubernetes environments from cloud to edge. Unify management and security while reducing operational overhead across your industrial facilities.

Enable long-horizon analytics and machine learning capabilities through AWS cloud services. Centralize operational intelligence while maintaining real-time edge performance across facilities.

How it works

These technical details feature an architecture diagram to illustrate how to effectively use this solution. The architecture diagram shows the key components and their interactions, providing an overview of the architecture's structure and functionality step-by-step.

Download the architecture diagram

Disclaimer

The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.

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