Resume Parsing

AI-powered data extraction from any resume format

Our AI parsing engine uses advanced language models to read and understand resumes in PDF or TXT format. It doesn't just extract text - it comprehends context, identifies sections, and structures raw content into clean, actionable candidate data you can immediately use for evaluation.

How it works

1

Upload

Drag and drop or select a resume file. We support PDF and TXT formats up to 10MB.

2

Extract

The AI reads the full document, identifying names, contact info, work history, education, skills, and certifications.

3

Structure

Raw text is transformed into a clean, structured profile with categorized skills, timeline-ordered experience, and education details.

4

Review

You see the parsed profile in a clean card layout, ready for the next step: scoring against a job description.

Key Capabilities

Multi-Format Support

Handles PDF and TXT files, parsing through varied resume layouts and styles.

Contextual Understanding

The AI understands job titles, company names, and duration from natural language descriptions.

Structured Output

Returns organized JSON with name, email, phone, location, summary, skills, experience, and education.

Fast Processing

Most resumes are parsed in under 10 seconds, even complex multi-page documents.

Under the Hood

Supports PDF parsing via pdf-parse library with fallback handling
LLM-powered entity extraction using free models (Llama 3.3, Gemma 3, Mistral Small)
Handles messy formatting, tables, columns, and non-standard layouts
Extracts skills as individual tags for granular matching
Groups experience entries with company, title, duration, and bullet highlights

See it in action

Try resume parsing now with our full AI pipeline.

Launch Pipeline