Case Study

Cloud Modernization & DevOps

DevOps and Cloud Automation for AI/ML based solution

NutaNXT built a complete software development infrastructure (IaaS) for an AI/ML-based system to automate the development and deployment of software models.

Client Introduction

A US-based disruptive start-up needed a cloud based solution with workflow to handle large volumes of IOT data and enterprise level machine learning capabilities.


Technologies Used By NutaNXT

  • DevOps
  • AWS
  • Microsoft Azure
  • AI & ML solutions

Use Case Applicable To Verticals

  • Multiple Industries

Code Release Duration

36 Hours

>=

 

Downtime

48 Hours

Client
Challenge

The client wanted to optimize its infrastructure by utilizing automation tools and DevOps best practices to better manage vast amounts of data and improve products and services for its customer base with increased scalability.

Key challenges with the existing model were:

  • Their requirement could be solved with an integrated software stack for edge/on-premises computing
  • Fully automated CI/CD pipelines to capture data and apply AI/ML tools in the cloud.

Team we built

  • 1
  • Data Scientist
  • 1
  • Cloud Architect
  • 2
  • DevOps Engineers

Our Solution

We established a dedicated Data Science Team to rapidly deploy Predictive ML models. 

  • We set up an environment on AWS to support stringent availability, processing time, latency, and accuracy requirements, critical to the product value proposition.
  • A similar setup on Azure was completed enabling the client to continue with the business and yet maintaining the system up-time requirements, as requested by the client.

Technology Stack Used

Code Release Duration Reduced To

4 Hours

>=

 

Downtime

Reduced To

6 Hours

Business Impact and Results

The solution helped accelerate developer agility, business productivity and enhance IT operational efficiencies by continuous delivery of applications, features, and functions at scale and increase in business value.

  • 4 hours of code release and deployment. 
  • 6 hours of downtime

More Works

From MVP to end-to-end digital products, our culture of intelligent innovation and engineering excellence have solved complex Digital Product Engineering challenges and delivered maximum business ROI for our clients.