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Streamlining Product Extraction and HS Code Mapping
Our client, a global consulting firm, faced challenges in developing an accurate model for their public sector client. They enlisted the help of our Data Analytics team to transform a substantial dataset of 200,000 purchase records from various sources. The goal was to extract the purchased products and perform a precise and efficient assessment of HS Codes based on country classifications.
The team began by reducing the dataset, achieving a 40% impact through data cleaning and preprocessing, filtering irrelevant information, and eliminating duplicates. They clustered and removed certain service activities and medical products. They then used natural language processing to convert activity descriptions into concise product names and mapped HS Codes to products with OpenAI’s GPT-4, ensuring accurate mapping.
By leveraging the combined power of AI and data analytics models, the client achieved high accuracy and efficiency in product classification, significantly reducing manual effort and time. In conclusion, the collaboration with the global consulting firm led to a streamlined process for product extraction and HS Code mapping, highlighting the effectiveness of AI-driven solutions in addressing complex data challenges.