Local Content Consultant

• Problem Statement

• Local content evaluation is often performed manually

• Inconsistent interpretation of local content regulations

• Time-consuming calculations and documentation

• High risk of human error and non-compliance

• Limited visibility for decision-makers

• Proposed Solution

An intelligent digital consultant that:

• Analyzes project and contract data

• Automatically calculates local content percentages

• Evaluates compliance against regulatory requirements

• Extracts and interprets policy rules using AI

• Provides actionable recommendations to improve local content

• System Workflow (Project Steps)

1- Data Input

Users provide:

• Project or contract details

• Supplier and vendor information

• Cost breakdowns (local vs non-local)

• Applicable local content requirements

2- Data Processing

• Data validation and cleaning

• Classification of cost components

• Standardization of formats and inputs

3- Analytical Engine

• Automated local content calculations

• Rule-based and data-driven analysis

• Benchmarking against compliance thresholds

4- AI Intelligence Layer

• Natural Language Processing for contract and document analysis

• Large Language Models (LLMs) to interpret regulations and requirements

• Retrieval-Augmented Generation (RAG) for grounding AI responses in official policies and guidelines

5- Evaluation & Scoring

• Clear local content score generation

• Compliance status classification (Compliant / Partially Compliant / Non-Compliant)

• Identification of gaps and improvement areas

6- Smart Recommendations

• Suggestions for increasing local sourcing

• Alternative compliant supplier options

• Strategic insights for future project planning

7- Output & Reporting

• Structured and easy-to-read reports

• Executive summaries

• Exportable outputs (PDF / Excel)

• Decision-ready insights for stakeholders

  
  

• Technologies Used

• Python for data processing and analytics

• Large Language Models (LLMs) for text understanding and reasoning

• RAG Systems for policy-grounded AI responses

• FastAPI for backend services

• Web-based UI for user interaction and reporting