HAFR Hiring Assistant for Recruiters

HAFR is a web application that provides automation to the HR department of organizations for recruiting the right person according to the job description by using the screening based on automated interviewer without involving any human biases and field professionals. It is a web application, so it a

Project Title

HAFR Hiring Assistant for Recruiters

Project Area of Specialization

Artificial Intelligence

Project Summary

HAFR is a web application that provides automation to the HR department of organizations for recruiting the right person according to the job description by using the screening based on automated interviewer without involving any human biases and field professionals. It is a web application, so it also gives the advantage of remotely interview without the limitation of the time zones. It saves a lot of time for the organization and gives the right employee according to their requirement. To help you solve this talent acquisition bottleneck, we created this comprehensive step-by-step guide on how to effectively, efficiently, and accurately shortlist candidates to move forward in your recruitment process and then selected the best one. HAFR solves the classic challenges of recruitment remain including how to screen and shortlist candidates.

The target market segment includes all middle- and large-income organizations. The recruiters have easily adapted to this recruitment change and it will be very helpful in recruiting for the right applicant. We are new to this technology, but we will align with one or more recruitment systems that will help us penetrate the market with this new technology.

Project Objectives

A lot of time requires for the selection of the Right employee in Shortlisting, Calling, Scheduling, and Interviewing.  Discrimination and biases in the selection process. Hire a field professional for the best recruitment is expensive. The Hiring Assistant for Recruiters Is a software Product (HAFR) That provides the ability to the Human resources department to hire the right applicant without any biases. Unlike currently available recruitment systems that do not support the fully automated system, it only provides the chunks of automated-system and needed a human for a technical interview. HAFR will develop this client-server system to help you solve this talent acquisition bottleneck, we created this comprehensive step-by-step guide on how to effectively, efficiently, and accurately shortlist candidates to move forward in your recruitment process and then selected the best one. HAFR solves the classic challenges of recruitment remain including how to screen and shortlist candidates based on automated interviews by machine. Our product will provide efficiency of making the selection decision with assistance from technology, improving the selection process by training the machine instead of interviewers, building recruitment strategies to increase the predictability of the right applicant.

Project Implementation Method

In this era of Advancement, we used the professional development IDE Pycharm with a framework of Django. Django gives us a massive number of built-in functionalities. As seen in the remote usage by candidates, we used the firebase for database development.

The implementation starts with the Admin panel and here the HTML5 and the web front_end languages are used. Admin uploads the candidate and question-answer repositories. A unique ID and password would be generated and assigned to all candidates then the candidates receive an invitation mail. Mail would have an interview site link with the candidate's credentials. This mentioned process requires basic to advanced python logic building and understanding.

Candidates will login by the link and the facial recognition algorithm recognizes the candidates to continue. For this purpose, we used digital image analysis, and advance level machine learning.

The Voice recognition algorithm will convert question text to speech and candidates will listen to them and then answered them verbally, these answers converted from speech to text. For this task, we used google APIS like Speech Recognition.

The evaluation process is the backbone of the project and here Deep NLP is used, for this task, we are using the BERT algorithm, which is a transformer-based algorithm used to find semantic similarity between the sentences. Bert is also a huge step forward in the development of search engines.

Benefits of the Project

Problems:

Recruitment and selection are critical human resources functions for business. The recruitment and selection process are a dynamic, complex, and important part of human resource management in organizations.

Hiring the right employees for your business can positively affect your turnover rate, company culture, production, and bottom-line profit.

Shortlisting is often the most challenging and time-consuming step in the recruitment process.

It has caught the attention of both practitioners and researchers over the last century with efforts for continuous improvements and research for best practices in interview and selection processes being explored.

Discrimination and biases in the selection process.

People do prefer by judging personal preferences religion, color, gender, etc.

Discrimination is a common problem in recruitment. Thousand of cases are registered against discrimination at recruitment.

Hire a field professional for the best recruitment is expensive.

Candidate assessment costs. Fees for companies that offer pre-employment CV Screening.

External recruiter expenses. Money spent to pay individual recruiters, recruiting agencies or staffing firms.

 Employer branding efforts. Funds spent on events related to recruiting, like campus recruiting days and careers    fairs.

Benefits:

Automated interview resolves discrimination issues a hundred percent.

As machine randomly speaks questions so it will hit every concept of the field.

Remotely interview resolves the issue of availability.

Hundred of interviews could be conducted at a time.

Revenue is saved and time regarding the whole interview procedure is saved.

Technical Details of Final Deliverable

Project Deliverables Modules:

Upload Interview Requirements:

 The HAFR should allow admin to upload the repositories of question and answers given by Hr_manager.

Upload Candidate Information:

 The HAFR should allow admin to upload the repositories of candidate given by Hr_manager.

Send Invitation:

 The system should send invitation contains an interview link, user id and password via email addresses provided though candidate information.

Record Interview Video:

 The system should record the video of the whole interview for the satisfaction of the Hr_manager.

Interview Verbally:

 The system should ask multiple questions verbally like a human and the candidate gives the answers to that questions in a limited time.

Evaluate Interview:

 The system should evaluate every question at runtime based on multiple answers provided in question-and-answer repository.

Shortlist Candidates:

 After the evaluation, system should shortlist the candidates.

View Shortlisted Candidates:

 The HAFR should allow Hr_manager to view shortlisted candidates for the job.

Final Deliverable of the Project

Software System

Core Industry

IT

Other Industries

Education

Core Technology

Artificial Intelligence(AI)

Other Technologies

Others

Sustainable Development Goals

Gender Equality, Industry, Innovation and Infrastructure

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com