How AI Structures and Optimizes Product Data

Modern businesses accumulate massive volumes of data, but without an appropriate structure, this information remains underutilized. The challenge is therefore to transform raw data into a strategic asset to facilitate decision-making and optimize business processes. Artificial intelligence (AI) now offers effective solutions to organize, clean, and harmonize this data on a large scale.

Project Context

Our client, a major player in the construction of civil engineering machinery, faced a critical problem:

A considerable volume of data: Over 3 million product entries to process.
A need for multilingual structuring: This data was in French and English, with inconsistencies between nomenclatures.
A high quality requirement: Data integration had to be flawless to ensure a smooth migration to a new technical platform.

Faced with these challenges, a manual solution would have been lengthy, tedious, and error-prone. AI represented an effective and scalable alternative.

Challenges of Processing Massive Data

Manual processing of large volumes of data presents several limitations:

Slowness and high costs: A human team would have taken months to analyze and harmonize these millions of entries.
Risk of inconsistencies: Human errors are inevitable when comparing and adjusting thousands of lines of data.
Difficulty adapting to future changes: A rigid structure would have posed problems in case of adding new languages or modifying nomenclatures.

Using AI addressed these issues by providing a flexible and automated solution.

The AI Solution Implemented

We developed a solution in three key steps:

1. Data Cleaning and Filtering

AI was trained to automatically identify and correct anomalies, such as duplicates, input errors, and syntax inconsistencies.

2. Multilingual Harmonization

Using natural language processing (NLP) algorithms, we established a correspondence table between French and English terminologies. The goal was to ensure perfect consistency between product descriptions.

3. Integration and Flexibility

Finally, we designed an intelligent workflow that allows the database to be easily adapted to future modifications or the addition of new languages.

Results Achieved

Thanks to this AI-based approach, our client obtained immediate benefits:

Significant time savings: Over 10 days of processing saved.
Optimized data quality: A harmonized database ready for integration without further adjustments.
Guaranteed scalability: The solution is adaptable for future projects without requiring a complete system overhaul.

Why Adopt an AI Strategy for Data Management?

If your company handles large amounts of data, AI can provide concrete solutions to:

Accelerate processing and structuring of information.
Ensure better precision and homogeneity of databases.
Facilitate integration into complex technical platforms.

Conclusion

AI is no longer an option but a necessity for optimizing data management in businesses. By automating cleaning, harmonization, and integration, it transforms volumes of raw data into a powerful strategic asset. At Strat37, we support our clients in this transition towards intelligent and efficient data utilization.

Would you like to learn more about our data optimization solutions? Contact us for a personalized demonstration!