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EXP-04CATEGORY: AutomationSTATUS: PROTOTYPE

Intelligent Document Pipeline

Multi-modal vision-language document processing engine for extracting structured data from unstructured enterprise forms.

EXPERIMENTAL OVERVIEW & OBJECTIVE

A high-throughput document extraction system capable of processing scanned PDFs, invoices, and handwritten forms into clean JSON schemas.

The Research Challenge

Legacy OCR software fails when layout structures vary or when document images contain low contrast or non-standard tables.

Engineering Approach

We utilize multi-modal vision-language models combined with schema validation to extract key-value pairs and tabular data automatically.

SYSTEM ARCHITECTURE SPECIFICATION

Vision-Language Model Parsing

Dynamic Bounding-Box Detection

Pydantic Schema Validation

Automated Exception Flagging

CURRENT BENCHMARK STATE

Processing 50,000 test invoices with a 98.6% field extraction accuracy rate.

FUTURE ENGINEERING DIRECTION

Integrating zero-shot document classification for multi-page packets.

TECHNOLOGY STACK & INFRASTRUCTURE
PythonPyTorchFastAPIDockerPostgreSQL

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