What would you do if you had to process millions of documents daily?

Consider These Scenarios

An insurance enterprise needed to generate thumbnails for over 10 million customer documents daily. Meanwhile, a utilities organization faced the challenge of processing over 2.5 million multi-page documents daily using Optical Character Recognition (OCR) to ensure they were fully searchable.

Faced with these monumental tasks, what would you do?

1. Employ a team of dedicated staff to manually process each document
2. Develop a proprietary, in-house IT solution
3. Invest in a document conversion and automation platform
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Let’s unpack these options:

Option #1: This approach is fraught with high operational costs, inefficiencies, and risks. Manual handling not only slows processes but also introduces human error, which could lead to legal consequences or delays in meeting critical deadlines.

Option #2: While potentially effective, building an in-house IT solution demands extensive resources for development, training, upgrades, and integration. The risk? Distraction from core objectives and creating a system that may not scale as enterprise needs evolve.

Option #3: Both enterprises chose this route, leveraging Adlib’s document conversion platform. The result? Enhanced scalability, reliability, and the ability to focus on their core business while allowing experts to handle the heavy lifting of document processing.

Why Multi-Processing Platforms are the Key to Scaling Enterprise Document Conversion

Traditional single-threaded systems process tasks sequentially, creating bottlenecks. These systems often follow a First-In-First-Out (FIFO) model, where critical documents get stuck behind large, time-consuming files.

To quantify the efficiency gained by transitioning to multi-processing, our team conducted benchmarking tests. Here’s what we discovered:

Benchmark Setup

• Equipment Specifications:
  
  • VMs: 4 CPU / 16 GB RAM (D4ads_v5 in Azure)
  • Disk Speed: Premium SSD @ 2300 IOPS (150 MB/s)
 
• File Batch Specifications:
  
  • Batch 1: 20 unique Word documents × 5 = 100 document
  • Batch 2: 100 unique PDFs × 2 = 200 documents
  • Batch 3: 50 unique MSG files with attachments × 2 = 100 documents
  • Batch 4: 20 PowerPoint presentations × 5 = 100 documents
  • Batch 5: Mixed (40 Word docs, 40 PDFs, 20 MSG files) = 100 documents
 
• Processing Steps:
  
  • Full-fidelity PDF conversion
  • Watermark stamping on each page
  • Bookmarking
  • Hyperlink preservation

Performance Results for Mixed Document Types

1. Single-Thread Architecture:
   
   • Throughput: 38k pages per hour
   • Queue Time: Average 100 seconds per job
   • Processing Time To 1 Million Pages: ~26 hours
 
2. Multi-Thread Architecture:
   
   • Throughput: 123k pages per hour
   • Queue Time: Average 20 seconds per job
   • Processing Time To 1 Million Pages: ~8.5 hours

Key Gains:

• 3.5x Speed Improvement: Parallel processing boosted throughput by 221%.
• 80% Queue Time Reduction: Critical documents now face minimal delays.

For the insurance enterprise described earlier, a multi-threaded system capable of handling 10 million multi-page documents daily would require 16 multi-processing engines at similar configurations to meet demand efficiently.

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OCR Performance Test

Separately, we tested our single and multi-processing environments for OCR speed. We learned that by upgrading your VM to multi-processing and scaling up to 6 instances, your organization can gain a 400+% processing speed without increasing your TCO.

Outside of Enterprise-grade Performance, What Else to Look for in a Document Automation Platform?

When selecting a document processing platform, consider these critical features:

• Conversion Fidelity: Does the system ensure high-quality, full-fidelity output, maintaining original document integrity?
• Scalability: Can it elastically scale with your organization’s needs, supporting enterprise-grade operations?
• Format Flexibility: What types and formats of files (e.g., DOCX, PDFs, MSG files, CAD, TIFF, Legacy) are supported?
• Advanced Features: Does it offer publishing functionality like watermarking, bookmarks, or hyperlink maintenance?
• Automation Capabilities: Can it merge documents, add metadata, or perform OCR to make images searchable?
• Performance Metrics: Does it deliver faster processing speeds with minimal wait times?
• Compliance Options: Support for specialized PDF formats such as PDF/a or PDF/x.
• Monitoring Tools: Real-time job management, reporting, and auditing.
• Job Prioritization: Can the system accommodate metadata-based rules for job priority assignments and process higher priority jobs ahead of transactional jobs?
• Interoperability: Can the system connect to all key line of business applications or only lives inside a DMS environment?
• Data Extraction: Can the system perform AI-based data extraction and document summarization?
• Robust Roadmap: Is the system being regularly updated with new critical functionalities and how close are customers to helping drive the roadmap?
• Customer Support: What SLAs and technical support infrastructure are provided?

By choosing the right technology partner, enterprises can transform their document workflows from a bottleneck to a competitive advantage, achieving cost efficiency, operational excellence, and future-proof scalability.

How many documents does your enterprise need to process in a day? Connect with our team to estimate how efficiently Adlib can do it for your organization.