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Our latest case studies

From On-Premises Data Center to Cloud: Five Star’s Strategic Shift to AWS Cloud Boosts Business Resilience

We at 1CloudHub successfully containerized an identified application, optimizing the cloud resources used by the application, for continuous delivery.

Elevating Financial Operations & Security with AWS Migration​

Industry Financial Solution CloudAWSPublished OnDec, 2024 About the client A leading financial services firm, aims to migrate its on-premises infrastructure to AWS to enhance security and align with financial industry compliance standards. The project involves assessing the current infrastructure, deploying AWS landing zone, designing a secure AWS architecture with VPCs, encryption, IAM policies, and threat[...]

Migration of SAAS Smart Carbon Measurement and Management Platform from Azure to AWS

Industry Carbon Measurement and Management CloudAWSPublished OnDec, 2024 About the client A prominent enterprise-grade SaaS platform specializes in smart carbon measurement and management. It provides comprehensive solutions to track and manage carbon emissions, enabling organizations to efficiently monitor, measure, and reduce their carbon footprint. Project Requirements: A leading SaaS provider in carbon management seeks to[...]

Our latest blog posts

Materials Identification System Development at Edge

Materials Identification System Development at Edge

This blog illustrates leveraging Amazon SageMaker and Amazon IOT Greengrass to develop an Image Classification ML model and deploy it on the Edge to detect objects.

Revolutionizing Document Processing with 1CH and Amazon Textract

Revolutionizing Document Processing with 1CH and Amazon Textract

In this blog, We will explain how 1CH improvised the functionality of Amazon Textract by developing a custom workflow solution by integrating with AWS Step Functions, AWS Lambda and AWS SNS making the above super-sized documents process easier and quicker.

Train and host custom-built Scikit-Learn model container in Amazon SageMaker

Train and host custom-built Scikit-Learn model container in Amazon SageMaker

How we can create our own container and import our custom Scikit-Learn model onto the container and host, train, and inference in Amazon SageMaker

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