Type
AI-based HR Recruitment Portal
Objective
One of the leading HRtech companies based in the United States wanted to automate his recruitment process by way of maximizing the accuracy and efficiency of matching candidate profiles to available job openings. Their core idea was to reduce time-to-hire and improve the candidate experience.
Technologies
React.js and Node.js with Express.js
Country
United States
Project Attributes
Engagement Model
Dedicated Team Engagement
Duration
6 months
App Users
Recruiters, HR managers, and candidates
Challenges
- High Volume of Applications: The client received an overwhelming number of apps for each job opening. Sifting through profiles manually was incredibly difficult.
- Inefficient Matching: Existing algorithms failed to accurately match candidates and lead to irrelevant profiles being shortlisted. Unnecessary time was utilized as well.
- Prolonged Hiring Process: Due to inefficient matchmaking, the time-to-hire was significantly high and impacted the client’s ability to fill crucial positions swiftly and productively.
- Poor Candidate Experience: Candidates felt neglected and the process was incredibly slow – leading to mismatches. The dissatisfaction ratio was high and reduced engagement.
Solutions
- AI-Driven matchmaking: We developed a robust AI algorithm tailored to the client’s needs. The algorithm was capable of analyzing resumes and job descriptions with high precision. The algorithm used Natural Language Processing to understand the ‘features’ of both candidate profiles and job requirements.
- Automated profile screening: This process involves automated systems for application screening, making it less labor-intensive. it reduces the time spent in filtering at the very initial stage. The system would filter profiles based on skills, experience, and relevance to the applied role.
- Personalized job recommendations: Integrated a feature that provided relevant job recommendations to candidates in order to enhance experience and engagement with the platform.
- Continuous learning: The AI model was designed in such a way that it continuously learns from the feedback provided by recruiters and becomes more accurate with time.
Results:
- Increased matching accuracy: Candidate-job matching accuracy has increased by 40%, ensuring more relevant profiles for recruiters.
- Reduced time-to-hire: The time-to-hire was reduced by 35%,and the client was able to fill positions faster and more efficiently.
- Enhanced candidate experience: Candidates reported a 25% increase in satisfaction due to more relevant job suggestions and quicker feedback.
- Operational efficiency: It resulted in bringing down manual work to the minimum for the client. Inevitably, that gave more time for the HR teams to engage in some other strategic tasks, which improved overall productivity.
Conclusion:
Adorebits’ AI solution not only met the client’s objectives but also positioned them as a leader in HRtech innovation, enhancing their recruitment process and overall business performance.