CLIENTDOCUMENT AI OCRWORKFLOW AUTOMATION•Human Resources
Automated HR Employment Document Processing Pipeline
AI-assisted intake pipeline that extracts, validates, and archives candidate employment records and contracts with 98% accuracy.
Key Outcome: 97% faster onboarding intake
Quick Facts
Timeline / Year
2026
My Role
Lead Engineer
Industry
Human Resources
Core Stack
Python, PaddleOCR, LangChain
The Business Problem
An HR department onboarding 200+ seasonal employees monthly spent over 40 hours per week manually transcribing citizen IDs, health certificates, and contracts into HRMS spreadsheets, suffering from frequent typographical errors.
Implemented Solution
Engineered an intelligent document intake pipeline with automated OCR preprocessing, LLM schema extraction, and human-in-the-loop review for low-confidence fields.
Role & Responsibilities
AI Automation Engineer: Implemented OCR image rectification, custom extraction prompts, webhook connectors, and validation rules.
Architecture & Implementation Details
Built an n8n processing pipeline that watches secure cloud intake folders, triggers OCR inference on GPU-enabled workers, normalizes Vietnamese accents and national ID numbers, and flags ambiguous records for human verification.
Verified Outcomes & Business Impact
Reduced candidate intake processing time from 25 minutes per applicant to 45 seconds, with an overall extraction accuracy exceeding 98.4% across 1,500+ processed documents.
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