Resume parsing

Document Processing

The Resume Parsing system leverages cutting-edge OCR technology combined with advanced NLP and LLM-based extraction to accurately parse and extract structured information from resumes in various formats. The system can handle PDFs, Word documents, and even scanned images, extracting key information such as work experience, education, skills, certifications, and contact details. It uses semantic parsing and NLP embeddings to understand context and relationships between different sections, ensuring high accuracy even with non-standard resume formats.

Completed20245 months

Project Overview

Client:HRTech Innovations
Duration:5 months
Team Size:6 developers
Status:Completed

Technologies Used

resume analysisOCR pipelinetext extractionsemantic parsingNLP embeddingsLLM-based extraction

Key Features

  • Multi-format document support
  • Intelligent field extraction
  • Skill and experience parsing
  • Education and certification detection
  • Contact information extraction
  • Structured data output

Challenges Overcome

  • Handling various resume formats and layouts
  • Extracting information from scanned documents
  • Dealing with non-standard resume structures
  • Ensuring accuracy across different languages

Results Achieved

  • 95% extraction accuracy rate
  • 80% reduction in manual data entry
  • 70% faster candidate processing
  • 90% time savings in resume screening