Abstract
A case study and technical report on designing an automated pipeline for rapid validation of large-scale legal contracts. Demonstrates how rule-based regex parsing combined with LLM semantic extraction reduced a 3-month manual auditing workload into a 3-week automated verification cycle.
Research Problem & Context
Fintech compliance requires verifying dozens of mandatory clauses, signature verifications, and regulatory stamps across hundreds of 30-page commercial contracts. Manual verification is error-prone and time-consuming.
Research Question
Can a hybrid pipeline combining deterministic OCR text pattern matching and language model parsing automate compliance checking across multi-page legal agreements?
Experimental Methodology
Processed PDF agreements using PyPDF2 / pdfplumber for deterministic extraction, cascading ambiguous edge cases to a local LLM parser with strict JSON schema outputs. Validated results against physical contract copies.
Software & Toolchain Stack
- Python 3.11
- pdfplumber / PyPDF
- Tesseract OCR
- Automated Regex Rule Engine
- Structured JSON Validation Framework
Experimental Setup & Testing
Sampled a calibration set of 20 contracts to establish the complete ground-truth rule matrix, then ran the pipeline across the contract batches with automated difference reporting.
Results & Analysis
The automated pipeline successfully identified missing signature fields and clause discrepancies, accelerating the auditing workflow while maintaining compliance standards.
Technical Limitations
Scanned documents with poor resolution required OCR preprocessing and manual review of low-confidence scores.
Primary Resources & Manuscripts
Citation Information
Cite this work
APA / Text:Alagha, A. (2026). Heuristic and AI-Assisted Multi-Page Legal Document Validation (Technical Report). https://abed.page/research/pdf-agreement-legal-automation
BibTeX:
@techreport{alagha2026pdfautomation,
author = {Alagha, Abedalraheem},
title = {Heuristic and AI-Assisted Multi-Page Legal Document Validation},
type = {Technical Report},
year = {2026},
url = {https://abed.page/research/pdf-agreement-legal-automation}
}