AI-Powered Hiring Platform
Data Science
2019 - ongoing
The US 
Angular|AWS|Django|Docker|PostgreSQL|Python|Ruby|Ruby On Rails
Custom software development|DevOps|Frontend Development
Dedicated team behind the project
The client
THE CHALLENGE
To create an AI-powered hiring platform, with the aim of automating 90% of the manual work involved in the recruitment process for recruiters, interviewers, and HRs. It was also important to ensure that the software development process was of the highest quality and followed best practices. This included conducting regular code reviews and minimizing technical debt.
what was done
Our objective was also to enhance the user interface of the platform. Through a detailed analysis of the existing workflow, we identified the platform’s vulnerabilities and developed solutions to address them.
One major issue we focused on was the manual process of completing profiles and CVs on the platform by job-seekers. This was a time-consuming task and could lead to errors in the submission of necessary data.
Another challenge was the lack of a further assessment option for companies to test the skills of the top candidates prior to an interview. The platform did not provide this option, which impacted the objectivity of assessments.
Implemented features
We streamlined the recruitment process by automating the manual tasks for both candidates and companies. With the improved platform, candidates only have to upload their CVs in pdf/doc/docx format and the platform will automatically fill in the corresponding fields, thus completing their profiles.Â
The platform now integrates with HackerRank, an independent assessment tool that offers the opportunity to conduct tests of various seniority levels for tech jobs within the platform.
After completing their profiles, candidates can assess their skills and knowledge by passing a test that matches their level, and the results are available in their profiles for employers to review.
We split front-end and back-end development using Angular and Ruby on Rails, resulting in a fast and responsive client-side UI.
Â
The existing Ruby on Rails programming framework was also updated to the latest version.
Additional features
- Third-party data sources for scoring to create AI knowledge metrics and suggest areas of improvement for candidates
- Broke up the fronted monolith to allow a faster and more responsive user interface
- A CV parsing tool was developed to extract relevant information from candidates’ CVs in pdf/doc/docx format
Results
of the recruitment process was automated
the time and cost associated with hiring AI specialists
the hiring process, making it easier for companies to find top AI talent
UX & responsiveness of the platform
Have a concept or facing a tech hurdle?
Share your thoughts. We’ll guide you through possibilities…
