Multimodal PDF Table Extraction with Intelligent Model Routing

Demo on request

Data Processing

This POC implements a multimodal PDF table extraction pipeline. PDFs are rendered as images, tables and text are extracted via vision-language models, and batches are routed to different LLMs based on complexity. Output is JSON/JSONL for downstream ML pipelines. Live execution is restricted because the system is under patent review.

System Screenshots

Key Capabilities

Intelligent batch routing for efficiency — automatically selects optimal LLM based on page count and complexity
Handles complex tables, nested headers, and mixed text with high extraction accuracy
Outputs structured JSON/JSONL ready for downstream ML pipelines and data integration
Patent pending / IP-sensitive implementation — core routing algorithms under intellectual property review

Interested in a private demonstration of this system?

Request full demo