Organizations regularly process technical manuals, reports, and lengthy documents that lack proper table of contents or structured navigation. To overcome the inefficiencies of manual indexing, the client needed an automated solution that could:
process PDFs without existing outline metadata.
handle multilingual and multi-format documents
generate accurate hierarchical document structure
maintain page number accuracy across hundreds of pages
validate outline quality automatically
scale to process documents with 1000+ pages
By automating the outline generation process, we reduced the time per dataset from 2 hours to 25 minutes - a 79% reduction - enabling nearly 5× higher throughput and faster data availability.
79%
Faster outline generation
5x
Higher throughput
2h
25min
Processing time
We built an intelligent dual-mode outline processing system integrating PDF parsing and Large Language Models (LLMs) to automatically transform unstructured documents into navigable, hierarchical content.
The solution was built around three key components:
Azure-based infrastructure ingests PDFs and automatically determines whether to use existing outline metadata or trigger AI-generated structuring. It ensures optimal processing for both simple and highly unstructured documents.
GPT-4 processes document text in batches, cleaning content, identifying hierarchical structure, and generating multi-level outlines (chapters, sections, subsections) with precise page references - even for documents exceeding 1,000 pages. The system uses YAML format for faster processing than structured JSON, allowing the LLM to iteratively refine and fix outlines in real-time as new document sections are analyzed.
LLM-based validation system checks every generated outline for structural integrity, meaningful section titles, and accurate page numbering - with confidence-based acceptance and automatic fallback mechanisms.
The system processes documents through a FastAPI backend with real-time progress tracking. It enables users to monitor outline generation from upload through completion, with results stored in PostgreSQL for instant retrieval and navigation.
The automated outline generation system delivers measurable value:
reduces manual indexing from hours/days to minutes,
ensures >95% outline quality thanks to LLM validation,
standardizes hierarchy across all document types,
handles both structured and unstructured PDFs,
processes documents of any size with automatic batching,
enables instant document navigation (each item includes precise page references).
The solution transforms document processing from a manual bottleneck into an automated, intelligent workflow - enabling organizations to unlock value from their document archives at scale.
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Schedule a call with Mark,
our Technical Solutions Manager
Write a message
mark.cameron@teacode.io
Postępu 15, 7th floor
02-676 Warsaw, Poland
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