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Development of Cloud-Native Supply Chain Optimization Platform with Scenario Analysis and Risk Management

kodius.com

Logistics

Information technology

Business services

Challenges in Supply Chain Design and Decision-Making

Existing supply chain solutions lack integrated cloud-native capabilities for simultaneous optimization, simulation, and risk analysis. Businesses struggle with fragmented tools that cannot efficiently process large datasets, model complex scenarios, or provide actionable insights combining cost, service, and risk metrics.

About the Client

A startup redefining supply chain design principles through innovative SaaS solutions

Objectives for Enhanced Supply Chain Platform

Create an intuitive cloud-native SaaS platform for end-to-end supply chain design
Enable multi-scenario analysis combining cost, service, and risk metrics
Develop scalable architecture to handle massive datasets with parallel processing
Implement commercial-grade MIP solvers for optimization accuracy
Deliver a user-friendly interface adaptable to diverse workflows

Core System Functionalities

Scenario modeling with hundreds of variables
Cost/service/risk trade-off analysis dashboard
Cloud-based storage architecture with hyperscaling
Visual workflow builders for supply chain modeling
API integrations for third-party data sources

Technology Stack Requirements

React

.NET Core

SQL

Azure

Python

External System Integrations

Commercial MIP solver APIs
Cloud storage management systems
Enterprise data warehouse connectors

Non-Functional Requirements

Horizontal scalability for parallel scenario processing
Sub-second response times for interactive dashboards
Enterprise-grade data encryption and access controls
99.9% platform availability SLA

Expected Business Impact of Supply Chain Optimization

Enables data-driven supply chain decisions reducing operational costs by 20-30%, accelerates scenario analysis from weeks to hours, and provides risk visibility for proactive mitigation. The platform's unique capabilities have demonstrated potential to attract significant investor interest, with early adoption showing $10M+ funding success.