How We Process 500+ Page Docs 90% Faster: Smashing 100MB Limits
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The Client: Apex Legal Partners
Industry: Corporate Law Challenge: Massive Document Overload & AI Limits The Bottleneck: The "Context Window" Wall
Apex Legal Partners deals with mergers and acquisitions (M&A). A single case can involve thousands of pages of scanned contracts, financial statements, and technical diagrams. They wanted to use AI to summarize these documents and extract key clauses, but they hit a hard technical wall: File Size Limits.
Standard AI models (like GPT-4 or Gemini) have "context windows"—a limit on how much text they can read at once. When Apex tried to upload a 500-page scanned PDF, the system would crash or hallucinate because the file was simply too big (often 100MB+).
Their paralegals were stuck manually splitting PDFs into tiny chunks, uploading them one by one, and then trying to stitch the AI's answers back together. It was a logistical nightmare.
The Solution: The "Infinite Scroll" OCR Engine
We didn't just build a chatbot; we built a heavy-duty document processing pipeline using n8n, Subworkflow.ai, and Google Gemini.
Here is the architecture that broke through the size limit:
Step 1: The Heavy Lifter
Standard automation tools choke on large files. We integrated Subworkflow via n8n to act as the heavy lifter.
Ingestion: When a file is uploaded to the firm's Google Drive, n8n grabs it.
The "Chunking" Process: Instead of forcing the whole file into the AI at once, the workflow sends the document (up to 100MB) to Subworkflow. This service intelligently breaks the document down into manageable "datasets"—page by page or section by section.
Step 2: The Polling Loop
Processing a 500-page PDF takes time. We couldn't just have the workflow "wait" and timeout.
We built a Smart Loop in n8n that checks the job status every few seconds. It essentially asks, "Are you done yet?" until the document is fully processed and ready for analysis.
Step 3: Multimodal Intelligence (Gemini)
Once the document was broken down, we fed the pieces into Google Gemini.
Because Gemini is "multimodal," it didn't just read the text; it could "see" the scanned images, charts, and tables in the legal documents.
It converted complex scanned pages into clean, searchable Markdown text, preserving the structure of the original contracts.
The Results
The impact on Apex Legal's operations was immediate:
0 Manual Splitting: Paralegals stopped wasting hours breaking up PDFs. They drop one massive file, and the system handles the rest.
100% Data Retention: Unlike previous attempts where pages were skipped due to size limits, this workflow processes every single page, ensuring no critical legal clause is missed.
Speed: What took 2 days of manual review now takes about 15 minutes of automated processing.
Automate Your Document Analysis
If your company deals with large technical manuals, financial audits, or legal discovery documents, you've likely hit the "file too large" error. We can build this pipeline to make your AI tools actually usable for enterprise-grade work.
