Navigating the "Paper Trail" of Global Trade

For a conglomerate dealing with large scale global shipments, the "last mile" of administration was a significant bottleneck. The company worked with a labor-intensive process of extracting data from complex, unstructured shipping documents and manually mapping them to specific bank forms.

• The Volume: 1,000+ complex documents per month (approx. 200/week).
• The Resource Drain: A dedicated team of 5 was required just to keep pace with 30 documents a day.
• The Velocity Cap: It took a skilled operator 60 minutes to process a single document.
• The Complexity: Documents were often poor quality (bad lighting/orientation), contained multi-page complex tables, and required dynamic reasoning, where data points changed context from one document to the next.

The Solution

A Hybrid "Small AI + Big AI" SaaS Architecture

The client partnered with Searce to build an Intelligent Document Processing (IDP) system on AWS. The strategy was to move away from a "blanket LLM" approach, which is often cost-prohibitive, in favor of a precision-engineered, dual-layer strategy.

1. Dual-Layer Intelligent Extraction

   • Layer 1 (The Specialist): Leveraged AWS Textract for initial OCR to handle standard data extraction at scale.
   • Layer 2 (The Strategist): For ambiguous fields or low-confidence scores, the system automatically routed data to a vision-enabled Large Language Model (LLM) via AWS Bedrock. This allowed for the "dynamic reasoning" required to interpret non-standard document formats.

2. High-Performance Infrastructure

   • Large File Handling: Engineered to process massive shipping dossiers (50MB–100MB) seamlessly uploaded via S3 pre-signed URLs.
   • Microservices Backbone: Built on AWS Lambda and API Gateway to ensure the system was decoupled, scalable, and resilient.

3. Optimized "Human-in-the-Loop" (HITL)

   To ensure a minimum 90% accuracy, Searce implemented RGB-Controlled Highlighting. Instead of an auditor reviewing the entire document, the UI highlights specific fields in yellow that require a "sanity check," focusing human attention only where it matters most.

Business Impact

By replacing manual entry with GenAI-powered automation, the company slashed document processing time by 83%, increasing daily productivity sixfold while maintaining a consistent accuracy rate of over 90%. This transition saved 167 man-hours weekly, allowing the team to scale from 5 to 30+ documents per person each day.

Key Takeaways

• Reclaimed Human Capital: What previously took a team of five an entire day to complete can now be managed in just 1 hour of focused review.
• Proportional Cost Savings: By reducing manual effort by 80%, the client successfully reallocated their expert workforce to high-value strategic tasks rather than data entry.
• Scalability: The system now handles 100MB documents with the same ease as a single-page invoice, future-proofing the client's global logistics pipeline.

Tech Stack

• Compute & Logic: AWS Lambda, API Gateway
• AI & ML: AWS Bedrock (GenAI), AWS Textract (OCR)
• Storage & Data: AWS S3, AWS DynamoDB
• Observability: AWS CloudWatch, IAM