Unlocking Legacy Systems: Using LLMs to Analyze Access Databases

research #llm 📝 Blog|Analyzed: Feb 6, 2026 05:00•

Published: Feb 6, 2026 04:49

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1 min read

Analysis

This article presents a brilliant approach to leverage the power of a Large Language Model (LLM) to understand and improve legacy systems built with Microsoft Access. By converting Access database components into text, developers can now utilize Generative AI to analyze and gain insights from these often-complex systems, streamlining the process of documentation and optimization.

Key Takeaways

•Access databases can be analyzed by converting their structure into text format.
•The process involves extracting VBA code, query definitions, table structures, and macro listings.
•This method enables LLMs to explain code, summarize logic, and suggest improvements.

Reference / Citation

View Original

"ChatGPT is unable to parse Access files directly. However, by converting the structure from MDB / ACCDB to text, analysis with LLMs becomes possible."

Qiita LLMFeb 6, 2026 04:49

* Cited for critical analysis under Article 32.

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