AI Resume Screening System
This project is an AI-powered resume screening solution built with Flutter and n8n. Recruiters upload multiple PDF resumes, the app extracts candidate information (name, email, skills, experience), and sends the data to an n8n webhook. n8n then calls an AI model (via Groq API), scores candidates, and returns structured results.
From your workflow image, the automation flow is: Webhook -> JavaScript -> HTTP Request (Groq) -> JavaScript -> Respond to Webhook -> If -> Gmail.
Rule implemented: if candidate score is greater than 80, the candidate is directly forwarded via email.
See It In Action
Real screens from the shipped product crafted for an intuitive, smooth, and delightful user experience.
Key Features
Multi-Resume Upload :
- Efficiency : Upload and process multiple PDF resumes in a single batch
- Workflow : Eliminates the need for individual file handling
- Utility : Designed to handle high-volume candidate screening in one run
Automatic Data Extraction :
- Automation : Instantly parses candidate names, emails, skills, and experience
- Accuracy : Digitizes unstructured resume content into structured data points
- Function : Reduces manual data entry for recruitment teams
AI-Based Candidate Scoring :
- Intelligence : Evaluates extracted profiles against job requirements via AI
- Objective : Provides a quantitative fit score for every candidate
- Analysis : Streamlines the initial screening process through smart assessment
Auto-Shortlisting Rule :
- Logic : Automatically identifies top talent based on a score threshold (>80)
- Speed : Pushes high-potential candidates directly into the communication flow
- Productivity : Focuses recruiter attention on the most qualified applicants
Email Automation :
- Connectivity : Sends automated Gmail notifications to top-scoring candidates
- Communication : Ensures instant engagement with short-listed talent
- Integration : Streamlines the transition from screening to the interview phase
Rich Result Insights :
- Analysis : Detailed breakdown of candidate strengths and weaknesses
- Preparation : Generates AI-suggested interview questions for each profile
- Visibility : Provides a comprehensive overview beyond a simple numerical score
Error Handling and Correction :
- Reliability : Displays parsing and API errors clearly for immediate troubleshooting
- Control : Ensures no data is lost due to technical or formatting issues
- Efficiency : Facilitates quick corrections to maintain the recruitment momentum
Third Party SDKs & Libraries
Carefully selected integrations powering this project's core functionality.
Have a similar idea?
Let's build it together.
From concept to launch we turn your vision into a world-class product. Get a free consultation today.