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Development of Scalable Inventory Management System with Real-Time Tracking and Predictive Analytics

shaligraminfotech.com

Business services

Information technology

Inventory Management

Challenges in Managing Large-Scale Inventory Systems

Existing inventory systems face critical issues including unresponsive user interfaces, data inaccuracy risks, fragmented enterprise data storage, scalability limitations in processing large datasets, lack of unstructured data handling capabilities, and recurring ETL/modeled data requirements. These challenges hinder operational efficiency and business scalability.

About the Client

A technology solutions provider requiring advanced inventory management software for multi-location operations and large-scale data processing.

Objectives for Inventory System Development

Implement automated inventory tracking with 99.9% data accuracy
Develop distributed data processing architecture for scalability
Create responsive UI/UX for seamless user experience
Establish real-time inventory visibility across multiple locations
Enable predictive analytics capabilities through structured data pipelines

Core System Functionalities

Real-time inventory tracking with barcode scanning
Automatic reordering and inventory alerts
Multi-location inventory management
Product listing with cost/price tracking
Serial number and raw material tracking
Interactive project chart visualization
Timesheet management integration
Data export capabilities

Technology Stack Requirements

ASP.NET Core

SQL Server

Web Application Architecture

System Integration Needs

Enterprise resource planning (ERP) systems
Logistics management platforms
Accounting software
Predictive analytics tools

Performance and Security Requirements

Horizontal scalability for 1M+ inventory records
99.95% system uptime SLA
Role-based access control (RBAC)
Data encryption at rest and in transit
Sub-second response times for critical operations

Business Impact Projections

Implementation will result in 40% reduction in inventory management overhead, 60% faster data processing times, and 90% improvement in inventory accuracy. The system will enable seamless scalability to support 500% business growth while maintaining operational efficiency through automated workflows and predictive analytics capabilities.