Project Overview
Our client, a US-based hiring intelligence company, needed to modernize its recruitment process by automating manual, time-consuming tasks. Confiz’s expertise in AI allowed the company to streamline recruitment for multiple roles, ensuring a more efficient and inclusive hiring experience. A comprehensive Proof of Concept (PoC) validated the system’s ability to enhance both the speed and fairness of the hiring process.
The need
The client, a US-based company with an online hiring platform, faced growing challenges, including processing large volumes of applications and reducing bias in candidate selection. Their current recruitment methods were labor-intensive and no longer efficient. Tasks like screening, interview preparation, and shortlisting required significant manual effort, often leading to delays and inconsistent hiring decisions.
To remain competitive and effective, the client needed an AI-powered system that streamlined recruitment and ensured accurate, unbiased candidate evaluations. Confiz aimed to modernize their platform, helping them connect talent to opportunities more efficiently.
The Solution
Confiz leveraged its extensive AI expertise to provide consultancy and implement advanced AI capabilities in the client’s hiring platform. A one-month Proof of Concept (PoC) validated AI’s ability to address key recruitment challenges.
Confiz identified that manually reviewing prerecorded interviews was a major bottleneck for the client. To address this challenge, we implemented a generative AI based model, deployed on AWS, which automatically processed interview transcripts, generating summaries and candidate ratings based on predefined attributes. The generative AI model also created highlight reels of 2 to 3 minutes from the interview videos, emphasizing the key segments of the interviews. This reduced delays in hiring, improved accuracy, and provided hiring managers with key insights into candidates’ aptitude for the role. This automated summary of interview transcripts and quantitative and qualitative evaluation of candidates was based on predefined attributes generated via generative AI models, such as GPT-4o.
Our team of ML engineers also developed interview guides using generative AI that allowed interviewers to plan and prepare for candidate sessions in advance. Another key feature developed was AI-based candidate fit scoring, where candidates were rated across predefined attributes. This ensured high accuracy, consistency in evaluations, and supported objective hiring decisions.
For data privacy, a data anonymization module was incorporated that ensured data protection. Moreover, our team conducted thorough QA to minimize AI hallucinations and enhance overall system reliability.
The Outcome
More inclusive hiring
The newly transformed AI-driven hiring system fostered a more inclusive hiring environment by promoting diversity and ensuring that candidates from all backgrounds were considered equally.
Reduced bias and objective evaluation
By leveraging AI insights, the platform minimized human biases, ensuring objective and data-driven evaluations based on predefined attributes.
Accelerating time-to-hire with process automation
By automating various stages of the hiring process, an average of 25 to 40 hours per job were saved, accelerating the time-to-hire.
Increased hiring efficiency
The AI-powered solution streamlined the recruitment process, reducing hiring time for managers and boosting efficiency by 50 to 70%, allowing them to make smart hiring decisions.
Consolidated candidate summary
The AI system generated summaries of key insights from interviews at a single interview level and across all interviews given by the candidate, giving hiring managers a clear overview of the candidate’s profile.
Freeing up strategic focus by automating tasks
By automating repetitive and low-impact tasks, the hiring teams were able to focus on strategic decisions, effectively reducing time-to-hire.
