Passion for improving hiring quality
In his role as a solutions architect, the founder Oras Al-Kubaisi has conducted more than 25 interviews in less than two months to hire a team of five.
Oras noticed how hard it is to conduct these interviews, even with more than 15 years of software engineering experience. It is not just the interview itself, and there are more aspects behind the scenes like:
- CV evaluation.
- Preparing questions related to the candidate experience.
- Explaining the role and how does it fit inside the team.
- Communicate expectations.
- Feedback to managers to speed up the decision process.
A quick search revealed that bad hires cost $240,000 in hiring, compensation and retention in the United States.
In the UK, a poor hire at a mid-manager level with a salary of £42,000 can cost a business more than £132,000 due to the accumulation of costs relating to training, lost productivity and more.
At this point, Oras started thinking of building an ATS to help startups avoid bad hires. The vision for that was to automate the tedious and time-consuming parts like:
- Generate job descriptions.
- Parsing CVs.
- CRM for applicants.
- Suggested interview questions based on the candidate CV.
- Interview scheduler tool.
- Feedback and notes.
The initial idea was to use job descriptions templates. Still, after brainstorming, the idea didn’t sound doable, especially collecting a tremendous amount of job descriptions, analysing which one is better and then predicting user input to select the right job description.
Even if the job templates idea were implemented, it would mean having the same static job description again and again.
From here, Oras started working with GPT-3 to validate the idea of generating job descriptions using the AI engine, which ended up being Job Description AI.
If something is repetitive, resources and time consuming then automate it. Free the time to focus on human interactions and creative work.