Decision Making in Raw Material Trade
An AI-driven data science solution helped a chemical trading company aggregate, standardize, and analyze complex global trade data, uncovering market trends and sales opportunities. This improved decision-making, enhanced competitiveness, and increased operational efficiency
The Challenge
A company specializing in trading chemicals needed to extract valuable insights from its vast and complex historical global trade data. With transaction records coming from multiple sources, in various languages and currencies, it was difficult to identify trade patterns, price trends, and potential sales opportunities.
The Solution
With Yukawa, the company implemented an AI-driven application that:
- Aggregates Data from Any Source: The system ingests transaction records from diverse sources, regardless of format, language, or currency.
- Cleans & Standardizes Information: AI automatically extracts relevant details, removes unnecessary clutter, and converts values into a unified format.
- Generates Actionable Insights: With structured, filterable, and easily accessible trade data, the company can now analyze trade patterns, track price fluctuations, and identify new sales leads.
The Result
With Yukawa, the company implemented an AI-driven application that:
- Aggregates Data from Any Source: The system ingests transaction records from diverse sources, regardless of format, language, or currency.
- Cleans & Standardizes Information: AI automatically extracts relevant details, removes unnecessary clutter, and converts values into a unified format.
- Generates Actionable Insights: With structured, filterable, and easily accessible trade data, the company can now analyze trade patterns, track price fluctuations, and identify new sales leads.