Document Processing
Eliminating 30K+ Document Backlog with AI Processing
Intersolia6 months
The Challenge
Intersolia faced a critical 30K+ document backlog across multiple formats PDFs that required manual processing. The existing workflow was consuming excessive resources, creating bottlenecks, and preventing scalable operations.
The Solution
Built an AI-powered document processing system using multiple language models in parallel. Developed a unique approach to break down complex documents into smaller components for efficient processing, with human-in-the-loop validation to ensure accuracy.
Our Approach
- 1Analyzed existing document patterns and processing requirements
- 2Developed a multimodal AI pipeline architecture
- 3Designed unique document dissection strategy for parallel processing
- 4Implemented multiple LLMs working in concert on document components
- 5Utilizing human-in-the-loop validation for quality assurance
Technologies Used
PythonDockerGemini AI
Results
- Backlog under control within 6 months
- 1,000+ documents processed daily
- >96% data quality ensured
- 3x increase in document throughput
30K+Documents ProcessedComplete backlog elimination
1K+Daily CapacitySustained processing rate
>96%Automated ProcessingData quality ensured
3xDocument ThroughputCompared to manual processing
Business Impact
- Integrated human-in-the-loop validation for quality control
- Enabled scalable document handling for future growth
- Created foundation for digital transformation initiatives
Key Learnings
- Importance of robust exception handling in production AI systems
- Power of asynchronous parallel processing to maximize AI quota utilization
- Critical role of stakeholder training in AI adoption success
- Value of thoughtful process design in decomposing problems for efficient AI use