Why Does HR Need AI? Unpacking the Problems and Solutions in CV Screening

Imagine you’re an HR professional in the middle of hiring season. A popular position opens, and suddenly, hundreds—if not thousands—of CVs flood your inbox. Manually sorting through them isn't just an exhausting marathon, it also opens the door to human bias and inconsistency. But what if this days-long process could be reduced to just minutes?

At Radya Labs, we tackled this challenge by building an intelligent CV Screener system. The goal was simple: design an automated system that filters candidates with up to 80% efficiency improvement, without sacrificing assessment accuracy.

How Does It Work?

To bring this idea to life, we created a straightforward workflow. Users (HR teams) simply upload two things: a job description (even in image format) and a batch of candidate CVs in PDF format.

The system then works behind the scenes:

1. Text Extraction: Text from the job description is extracted using OCR, while all text from each CV is parsed from the PDF files.

2. AI-Powered Analysis: These two sets of text are then fed into a Large Language Model (LLM). The LLM is given specific instructions to analyze each CV based on the job description’s criteria.

3. Structured Output: The results are displayed in a clean, structured table, complete with scores and pass/fail decisions for each candidate.

The LLM serves as the system’s core engine, and we use Google Gemini, integrated through the LangChain framework. This model has proven highly reliable for our use case, especially in generating structured JSON outputs with 98% consistency and an error rate below 2%. Its ability to match candidates to job criteria also shows strong accuracy at 92%. In terms of speed, the system is rated “Excellent” for handling large volumes of CVs simultaneously (batch processing), ensuring smooth performance even under heavy workloads.

 

 

An Intuitive User Interface

Of course, advanced technology is useless if it’s hard to use. That’s why we designed a highly intuitive and interactive web interface. Users will find three main sections: one for uploading job descriptions and CV files, one for viewing results in a sortable and filterable interactive table, and one for tracking real-time processing progress.

Tangible Business Impact

Our system is a game changer with measurable performance. Each CV is now processed in just 2–3 seconds, and the system can handle over 50 CVs at once. With candidate-job matching accuracy reaching 92%, we’re not just fast—we’re precise. This transformation has had a massive impact on HR workflows, drastically reducing manual screening time by up to 85%, tripling team productivity, and cutting screening costs by as much as 70%.

This CV Screener project proves that with the right architecture and carefully chosen AI technology, one of HR’s most exhausting processes can be transformed into a smart and efficient workflow. By automating repetitive tasks, HR teams can now focus on what truly matters: identifying and connecting with the best human talent.

 

 

Ready to transform your recruitment process with AI? Contact Radya Labs at contact page to explore how our solutions can help your HR team work faster and smarter, and don’t forget to visit the Radya Labs blog for more insights and innovations in AI-driven business transformation.