Enhancing Recruitment Quality Through an Intelligent Pre-Interview System

Imagine this scenario: a candidate with a seemingly perfect CV passes the document screening stage (see also our blog on CV screener here). However, during the interview, it becomes clear that the listed experience doesn’t match reality, or worse, the candidate doesn’t fully understand the position they applied for. Valuable time and resources are wasted on an unsuitable candidate.

This is a common gap in the recruitment process. Document screening alone is not enough to validate a candidate’s experience, understanding, and cultural fit with the company. To bridge this gap, the concept of a pre-screening interview was born.

But what if this crucial process could be made more efficient? That’s where artificial intelligence comes in. We introduce a solution: the Pre-Interview Bot, an intelligent system designed to automate the initial screening process, quickly, consistently, and accurately.

This bot prepares pre-interview questions for candidates based on company and job vacancy information provided by the recruiter, along with the candidate’s CV. It’s important to note that this bot functions within the scope of pre-screening, distinct from the actual interview. Its role is to make a quick assessment based on key indicators. The questions it generates are simpler than those in a full interview. With this bot, recruiters can focus their attention on candidates who are more likely to be a good fit for the company and the role.

How Does the Pre-Interview Bot Work?

The bot operates through a systematic workflow involving three main actors: the Recruiter, the Pre-Interview Bot, and the Candidate. In simple terms, the recruiter provides the “ammunition” in the form of job details, the bot sets up the “arena,” and the candidate completes the “challenge.”

Process Diagram Pre Interview Bot Workflow

Behind the scenes, the process is divided into three main stages:

Stage 1: Job-Specific Question Preparation

The first stage is all about preparation. The recruiter provides the bot with three key pieces of information: company description, job description, and job requirements. From these, the bot intelligently generates two types of questions:

Company-Specific Questions: Generated from the company description to explore the candidate’s alignment with the company's values and culture.
Qualification Questions: Generated from the job requirements to ensure the candidate meets the technical criteria.

Job Question Preparation for Pre Interview Bot Diagram

Once all questions are generated, the bot prioritizes them to form a standard question set to be asked to every candidate.

Stage 2: Candidate-Specific Adjustment

When a candidate submits their CV, the bot doesn’t stop at generic questions. Using the CV and job description as context, the bot generates personalized questions, tailored specifically for that candidate. These are designed to validate and dig deeper into the information listed on their CV.

Candidate Pre Interview Preparation for Pre Interview Bot Diagram

For example, if the general question set includes, “Are you comfortable working a 24/7 schedule?”, this might be replaced with a more specific question like, “What’s your experience using Technology Y to handle security incidents?”—assuming “Technology Y” is listed on the candidate’s CV.

Stage 3: Assessment Moment (Candidate Answer Analysis)

After the candidate answers all questions, the automatic evaluation begins. The bot analyzes the responses using all available information (company description, job requirements, and CV) to generate two primary scores:

Company Fit Score: Measures how well the candidate aligns with company culture and values.
Qualification Score: Measures how well the candidate meets the technical job requirements.

Pre Interview Assessment Process for Pre Interview Bot Diagram

Each evaluation includes an in-depth analysis along with scores, presented to the recruiter as a final report for each candidate.

Room for Improvement

Of course, this bot design is still in its early stages and has areas for further development:

Question Balance: Finding the right number of questions—simple enough to avoid exhausting candidates, yet complete enough for accurate assessment.
Avoiding Redundancy: Ensuring personalized CV-based questions don’t overlap with general ones.
Cheating Risk: The current system assumes candidates respond honestly without help from others or search engines.
Interactivity: Transforming the experience from a form-filling process into a more natural conversation—possibly evolving into voice or avatar-based interactions.
Effectiveness Validation: Measuring whether the generated questions and the resulting analysis truly help recruiters in real-world decision-making.

In Conclusion

The Pre-Interview Bot is designed with one primary goal: efficiency. By automating the initial screening process, recruiters can focus their time and energy on the most promising and suitable candidates.

However, no matter how advanced the technology, the human touch remains essential. This bot is a support tool, not a replacement. In the end, it is still the recruiter who will make the final decision in selecting the best talent to join the company.

Ready to Build an AI-Powered Recruitment or Business Solution?

If you're interested in developing a similar solution using AI, cloud technologies, or custom applications, feel free to reach out to Radya Labs via our contact page. We’d love to explore how we can help bring your ideas to life.

For SMEs looking to improve customer service through automated and efficient communication, get to know our omnichannel platform at jangkau.ai , designed to help your business respond smarter and faster across multiple channels.

References

What You Should Know About Interview Pre-Screening | michaelpage.com
Apa Itu Pre-Screening Interview? Ini Arti & Tahapannya! | msi-indonesia.com