Eliminating 'Manual Dependency' in Data Operations: Launch of 'YOROZU AI' for Automated Data Processing
Review Co., Ltd. has launched 'YOROZU AI,' a feature that automates data creation, processing, and organization using natural language instructions, eliminating the need for manual Excel labor.
📋 Article Processing Timeline
- 📰 Published: April 28, 2026 at 18:00
- 🔍 Collected: April 28, 2026 at 10:01
- 🤖 AI Analyzed: April 28, 2026 at 10:05 (3 min after Collected)
Review Co., Ltd. (Chuo-ku, Osaka; CEO: Shigeo Fujimoto) has launched 'YOROZU AI,' an AI feature within its 'YOROZU DATA' platform that allows users to create, process, and organize data using only natural language instructions. This feature aims to streamline the most time-consuming parts of data operations and shorten the process of making data ready for practical use. Previously, data operations relied heavily on manual work using Excel. YOROZU AI reduces this burden, providing an environment where anyone can handle data.
Behind data utilization lies 'invisible manual work.' Even as AI becomes more prevalent, many manual steps occur in the pre-processing stage. Common tasks include standardizing notation (e.g., matching 'Co., Ltd.' with '(Ltd.)'), deleting duplicate customer data, adding phonetic readings to names, unifying zip code/phone number formats, and merging disparate data sources into a single list. These tasks consume significant time and are prone to human error and personalization.
Data utilization ideally follows a flow of 'Acquisition → Processing → Utilization.' However, the processing stage often becomes a bottleneck—the 'last mile' challenge. YOROZU AI automates these manual-dependent tasks with instructions like 'delete duplicate rows' or 'add hyphens to zip codes.'
The tool covers three key challenges:
1. Addressing missing data by generating CSVs based on specific conditions.
2. Resolving the inability to organize data by executing formatting and deduplication via natural language.
3. Overcoming data fragmentation by merging different CSV files.
YOROZU DATA currently offers a 'First 300 items free' promotion for new registrants, allowing users to verify the tool's effectiveness with real-world data.
Behind data utilization lies 'invisible manual work.' Even as AI becomes more prevalent, many manual steps occur in the pre-processing stage. Common tasks include standardizing notation (e.g., matching 'Co., Ltd.' with '(Ltd.)'), deleting duplicate customer data, adding phonetic readings to names, unifying zip code/phone number formats, and merging disparate data sources into a single list. These tasks consume significant time and are prone to human error and personalization.
Data utilization ideally follows a flow of 'Acquisition → Processing → Utilization.' However, the processing stage often becomes a bottleneck—the 'last mile' challenge. YOROZU AI automates these manual-dependent tasks with instructions like 'delete duplicate rows' or 'add hyphens to zip codes.'
The tool covers three key challenges:
1. Addressing missing data by generating CSVs based on specific conditions.
2. Resolving the inability to organize data by executing formatting and deduplication via natural language.
3. Overcoming data fragmentation by merging different CSV files.
YOROZU DATA currently offers a 'First 300 items free' promotion for new registrants, allowing users to verify the tool's effectiveness with real-world data.