Ai_classify in Databricks

2026-02-17 · Source: Alex The Analyst · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Data Science & Analytics, Software Development & Engineering · Depth: Intermediate, medium

Summary

The Databricks `AI_CLASSIFY` function enables users to categorize unstructured data, such as PDFs, by leveraging AI to read document content and assign it to predefined categories. This process is demonstrated using a hospital scenario where unorganized medical documents (claims, lab reports, clinical notes, administrative documents, invoices) need automated classification. The method involves uploading various PDF files to a Databricks volume, parsing their content using `AI_PARSE_DOCUMENT`, and then applying `AI_CLASSIFY`. The function requires the document content as a string and a list of desired categories as an array. The article highlights the importance of defining specific and comprehensive categories to ensure accurate classification, showing how adding "administrative document" as a category improves the model's performance. This functionality is available on Databricks free edition, making it accessible for efficient data organization.

Key takeaway

For Data Engineers managing large volumes of unstructured documents, Databricks' `AI_CLASSIFY` offers a free, efficient solution for automated categorization. You should define a comprehensive and specific list of categories to ensure accurate classification, potentially integrating this into an ETL process to automatically move files into categorized storage locations. This can significantly reduce manual effort in data organization.

Key insights

Databricks' `AI_CLASSIFY` function automates document categorization using AI, streamlining unstructured data organization.

Principles

• Category specificity improves classification accuracy.
• Unstructured data can be programmatically organized.

Method

Upload documents to Databricks, parse content with `AI_PARSE_DOCUMENT`, then apply `AI_CLASSIFY` using the parsed content (cast as string) and an array of desired categories (e.g., ["medical claim", "lab report"]).

In practice

• Use `AI_CLASSIFY` for automating document sorting.
• Define granular categories for better results.
• Integrate into ETL for automated file separation.

Topics

• Document Classification
• Databricks AI Functions
• Unstructured Data Processing
• PDF Data Extraction
• ETL Processes

Best for: Data Scientist, Data Engineer, Machine Learning Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Alex The Analyst.