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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 # 30

AI Agent to Optimize Decision-Making in Supply Chain Planning​​

CodeBranch developed an AI agent that helps supply chain planners in a semiconductor and hardware company make smarter, data-driven decisions.

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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, two developers, a project manager, and a software architect.

Results

  • Faster Decision-Making: Reduced the time required for planners to evaluate options and act on operational data.

  • Context-Aware Insights: AI adapts recommendations to each stage of the supply chain, from demand planning to production scheduling.

  • Improved Accuracy: Enhanced forecasting and planning precision through real-time, data-driven analysis.

  • Operational Efficiency: Minimized manual effort while streamlining supply chain workflows.

  • Risk Reduction: Strengthened the company’s ability to anticipate disruptions and respond effectively.

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, involved creating an artificial intelligence agent to assist supply chain planners at a semiconductor and hardware company. The AI agent is designed to support daily decision-making and help users interpret operational data generated within the platform.

The solution is seamlessly integrated into the company’s supply chain processes, with the ability to understand the specific context in which the user is operating (e.g., demand planning, inventory management, or production scheduling).

 

By leveraging this contextual awareness, the AI agent provides tailored responses and recommendations, enhancing planning accuracy, reducing risks, and streamlining strategic decision-making.

Case Study # 29

What if scenario for an end-to-end Supply Chain

Case Study # 31

AI Helps Supply Chain Planners Prioritize Demand and Resources

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