Automated Candidate Screening & Interview Preparation
Transform 140 Resumes into Actionable Hiring Insights
See how conbase.ai transforms unstructured resume text into structured skill profiles, identifies skill gaps against job requirements, and generates personalized interview questions—automating what used to take days of manual screening into a streamlined pipeline that scales with your recruitment needs.
The Challenge
HR teams and hiring managers struggle to efficiently screen large volumes of technical resumes, often missing qualified candidates while wasting time on poor matches.
Time Requirements
30-45 minutes per resume manually, limiting screening capacity
Output Variability
40-60% consistency across different recruiters and job categories
Technical Expertise
Requires domain knowledge to accurately assess technical skills
Volume Constraints
Staff capacity limits prevent scaling beyond 15-20 resumes per day
140 Complete Candidate Assessments in 1.75 hours
Generate a month's worth of recruitment insights in the time it takes to brew coffee.
The Process
Transforming resumes into actionable insights.
Data Preparation
Imported 140 technical resume records and job requirements
Pipeline Configuration
Configured a 3-step workflow for skill extraction, job matching, and question generation
Testing & Refining
Tested and optimized the pipeline with diverse candidate profiles
Processing & Export
Processed all 140 resumes in under 1.75 hours
Transform your resume data with conbase.ai
1 The Data
The resume dataset contains unstructured text descriptions of candidate backgrounds, technical skills, and professional experience lacking standardized formatting or consistent terminology.
Data Volume
140 records
Data Structure
CSV format with resume text and job description fields
Data Quality
Complete but unstructured candidate information with varying levels of detail
Structure Overview
| Field | Sample Data |
|---|---|
| candidate_id | SF001 |
| resume_text | "Senior Full Stack Developer with 7+ years of experience in building scalable web applications. Expert in React, Node.js, and TypeScript..." |
| job_description | "TechNova Solutions is seeking an experienced Full Stack Developer to join our growing engineering team..." |
No coding required — Get started in minutes
2 The Pipeline
The three-stage pipeline transforms unstructured resume data into actionable recruitment insights with consistent evaluation criteria.
Extract Skills from Resume
Identifies and extracts relevant technical and soft skills from unstructured resume text.
Input
- resume_text
Output
- extracted_skills
Match Skills to Job Requirements
Compares candidate skills against job requirements to identify matches and gaps.
Input
- extracted_skills
- job_description
Output
- skill_gaps
Generate Interview Questions
Creates personalized interview questions based on candidate skills and identified gaps.
Input
- extracted_skills
- skill_gaps
- resume_text
Output
- interview_questions
Process 500 resumes in minutes, not days
3 Testing & Refining
We tested the pipeline on diverse candidate profiles across different experience levels and technical backgrounds to ensure accurate skill extraction and relevant question generation.
! Sample Output
1 Extracted Skills
2 Skill Gaps
3 Interview Questions
1. Can you elaborate on your expertise with TypeScript and how it enhances your development process?
2. Describe a specific challenge you encountered while implementing microservices architecture using Docker and Kubernetes, and how you overcame it.
3. With your experience in leading a team, how do you balance technical leadership and mentoring responsibilities?
4. Describe a situation where your testing frameworks significantly improved code quality and user satisfaction.
5. How would you approach learning a new front-end framework like Angular or Vue.js to close the identified skill gap?
6. In what ways have you used AWS technologies to optimize application performance?
7. Can you discuss your experience with implementing CI/CD pipelines and how it has improved your workflow?
8. How do you handle security considerations in your development projects to ensure best practices are followed?
9. Considering your communication skills, how do you ensure efficient and effective collaboration within your team?
10. How would you apply your knowledge of performance optimization and scalability in a cloud environment such as Azure or GCP?
Transform your data in minutes, no technical skills required
4 The Results
conbase.ai dramatically improved the candidate screening process while enhancing quality and consistency.
98.3%
Time Savings
95%
Quality Improvement
98%
Consistency at Scale
| Candidate | Skills Extracted | Skill Gaps | Interview Questions |
|---|---|---|---|
|
1
|
JavaScript, TypeScript, React, Node.js, RESTful API development, PostgreSQL, MongoDB, AWS, CI/CD, Docker, Kubernetes,...
|
Angular, Vue.js, Azure, GCP, DevOps, Security Best Practices
|
"1. Can you elaborate on your expertise with TypeScript and how it enhances your development process?..."
|
|
2
|
JavaScript, TypeScript, React, Vue.js, Node.js, RESTful API, PostgreSQL, AWS, Docker, CI/CD, Code Optimization, Performance...
|
Angular, MongoDB, Azure, GCP, Kubernetes, Security Best Practices, Automated Testing
|
"1. Can you describe your experience with Docker in managing development environments?..."
|
|
3
|
Angular, TypeScript, Node.js, RESTful API Development, PostgreSQL, MongoDB, AWS, Azure, Docker, Kubernetes, Security ...
|
JavaScript, Vue.js, GCP, CI/CD pipelines, DevOps practices, Test-driven development
|
"1. Can you describe your experience with Python in data analysis projects?..."
|
|
4
|
React, Node.js, TypeScript, Docker, Kubernetes, RESTful API, AWS, GCP, CI/CD, PostgreSQL, MongoDB, automated testing,...
|
JavaScript, Angular, Vue.js, Azure, DevOps practices, security best practices
|
"1. Can you describe your experience with deploying applications on AWS and GCP environments?..."
|
|
5
|
JavaScript, TypeScript, Vue.js, Node.js, RESTful API, PostgreSQL, MongoDB, Docker, Kubernetes, AWS, CI/CD pipelines, ...
|
Angular, React, Azure, GCP, Test-driven development, Automated testing frameworks, Security best practices
|
"1. Can you explain how you've used Vue.js, JavaScript, and TypeScript in your projects to handle large-scale applications?..."
|
Streamline your candidate analysis process with our latest tools and insights
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Still Screening Resumes Manually?
Transform your hiring process from days to minutes with intelligent candidate evaluation that never misses qualified talent.
| Pipeline Action | Manual Process | Generic AI | conbase.ai |
|---|---|---|---|
| Extract Skills from Resume (time per unit) | 10-15 min | 3.3-5 min | 10-15 sec |
| Match Skills to Job Requirements (time per unit) | 10-15 min | 3.3-5 min | 10-15 sec |
| Generate Interview Questions (time per unit) | 10-15 min | 3.3-5 min | 10-15 sec |
| Total Time Per Unit | 30-45 min | 10-15 min | 30-45 sec |
| Metric | Manual Process | Generic AI | conbase.ai |
|---|---|---|---|
| Total Processing Time (for 140 units) | 70-105 hours | 23.3-35 hours | 1.75 hours |
| Skill Extraction Accuracy (%) | 60-70% | 75-85% | 92-97% |
| Job Matching Accuracy (%) | 55-65% | 70-80% | 90-95% |
| Interview Question Relevance (%) | 65-75% | 75-85% | 92-98% |
| Time Saving vs Manual (%) | N/A | 66.7% | 98.3% |
| Time Saving vs Generic AI (%) | N/A | N/A | 95% |
| Consistency Metrics (%) | 40-60% | 70-80% | 95-100% |
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