This Case Shows Specific Expertise. Find the Companies with the Skills Your Project Demands!

You're viewing one of tens of thousands of real cases compiled on Many.dev. Each case demonstrates specific, tangible expertise.

But how do you find the company that possesses the exact skills and experience needed for your project? Forget generic filters!

Our unique AI system allows you to describe your project in your own words and instantly get a list of companies that have already successfully applied that precise expertise in similar projects.

Create a free account to unlock powerful AI-powered search and connect with companies whose expertise directly matches your project's requirements.

ShelfWise Application Enhancement & Stability Project

visuality.pl

Retail

Application Stability and Performance Challenges

ShelfWise, a rapidly growing provider of AI-powered auditing software, is experiencing challenges related to application stability and performance, particularly under heavy user load and during peak usage times. The existing architecture requires improvement to ensure reliable operation, scalability, and efficient data processing for its expanding customer base.

About the Client

ShelfWise is a technology company providing AI-powered auditing software for the retail industry, enabling faster and more accurate store display data collection and analysis.

Project Goals

Enhance the stability and reliability of the ShelfWise application.
Improve application performance, particularly under high traffic conditions.
Optimize data processing for the ML model to reduce latency and resource consumption.
Successfully migrate the application between cloud service providers with zero downtime.
Improve the overall scalability of the platform to accommodate future growth.

Functional Requirements

Enhanced data processing capabilities for faster SKU and pricing extraction.
Improved handling of high traffic loads during peak hours.
Seamless cloud migration with automated failover mechanisms.
Optimized data model utilization for efficient data retrieval.

Preferred Technologies

Ruby on Rails

React.js

EventDriven Architecture

Elasticsearch

RabbitMQ

Kubernetes

Integrations Required

Cloud platform APIs (AWS/Azure/GCP)
Potentially existing retail data systems (TBD)

Key Non-Functional Requirements

High Scalability
High Availability
Zero Downtime Migration
Robust Security
Performance under heavy load

Expected Business Impact

Successful completion of this project will result in a more stable, reliable, and scalable platform for ShelfWise. This will lead to improved customer satisfaction, reduced operational costs, and the ability to support future growth. The zero-downtime migration will minimize disruption to existing users, and enhanced performance will improve the efficiency of the auditing process for retailers.