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Docling Parser
The Docling parser is a third-party intelligent document parsing framework that brings together multiple open-source models for layout understanding and table extraction. Optionally, you can combine the Docling parser with image processing by using Large Language Models (LLMs) to enhance responses from information available in images.
For more information, see Docling parser.
Use the Docling parser to parse content that contains information in these formats.
| Parser Option | Format | Description | Extension |
|---|---|---|---|
| Docling | Document | Structured content such as text and complex tables in documents. | .pdf, .docx, .doc |
| Spreadsheet | Spreadsheet data in cells, rows, and columns. | .xlsx, .xls | |
| Slide Deck | Content in presentations such as PowerPoint. | .pptx, .ppt | |
| Web Page | Content in websites. | .html, .xml, .xhtml, .htm | |
| Docling + LLM-Based Image Processing | Image File | Content in images, diagrams, and flowcharts. Parse images using LLMs by turning-on the image-processing toggle when you define chunking strategies. | .png, .jpg, .jpeg, .bmp, .tiff, .tif, .gif, .pdf |
You can’t select both the Docling parser and LLM-based Visual Data Pre-processing options for a search index. To parse images using an LLM, turn on image processing when you select chunking strategies.
For more information on configuring content parsing with Data 360 search indexes, see Create a Vector Search Index with Advanced Setup and and Create a Hybrid Search Index with Advanced Setup.
Consider an airline maintenance division that manages operational processes through structured RACI-style flowcharts within its governance manuals. These process maps define critical handoffs and validations across functions such as operators, reps, modules, planning, and operations. Each diagram includes directional arrows, decision nodes, and annotated swim lanes, reflecting step-by-step responsibilities from irregularity detection through to work plan reprioritization and resource redistribution.
With this enhancement, the LLM can interpret the flowchart as a structured process, recognizing nodes, connectors, arrows, and step order. Instead of a flat list of labels, the LLM reconstructs the sequential flow of actions across roles and departments. As a result, answers to questions from the field related to responsibilities or the sequence of steps are more accurate.
