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Software Development for Industries

We create dedicated teams of developers to accomplish our partners' goals in any industry. Find on this page some examples. 

Case Study # 29

What-if scenario assessment for an  end-to-end supply chain​​

A CodeBranch team built a platform for a semiconductor and hardware company to simulate and analyze what-if scenarios across its supply chain

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Industries

Services Provided

Approach

The technologies used in this project are:​​

- React

- Nest.js 

- Next.js

- Python

- PostgreSQL 

- FastAPI

- LLama

The project team included a UX/UI designer, one QA specialist, four developers, a project manager, and a software architect.

Results

  • Improved Planning Accuracy: The platform increased the accuracy of production forecasting by enabling data-driven evaluations of multiple what-if scenarios.

  • Reduced Decision-Making Time: AI-assisted analysis significantly shortened the time required to assess supply chain contingencies and alternatives.

  • Risk Mitigation: By simulating demand fluctuations and operational constraints, the company enhanced its ability to anticipate disruptions and minimize risks.

  • Operational Efficiency: Automated scenario creation and data interpretation streamlined supply chain planning, reducing manual effort and errors.

  • Strategic Agility: The organization gained the capability to adapt quickly to market changes, strengthening competitiveness in the semiconductor and hardware sector.

Ratings

Quality : 5.0/5.0

Cost:  5.0/5.0

Schedule : 5.0/5.0

Willing to refer :  5.0/5.0

Overview

This project, developed by a dedicated CodeBranch team, focuses on building a specialized platform to evaluate potential scenarios within the supply chain of a semiconductor and hardware company. The tool enables production forecasting by considering different strategic objectives, demand variations, operational constraints, and potential contingencies. In doing so, it allows the simulation and analysis of multiple what-if scenarios, supporting planning and decision-making through accurate data and reliable projections.

A key differentiator of this platform is the integration of an artificial intelligence agent, implemented by CodeBranch’s development experts. The AI not only assists users in constructing hypothetical scenarios but also interprets the generated information. This delivers actionable insights that optimize end-to-end supply chain management, reduce risks, and enhance responsiveness to market changes.

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Case Study # 30

AI Agent to Optimize Decision-Making in Supply Chain Planning

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