The “people” are the key differentiator who plays an integral part in driving competitive advantage for businesses. In a competitive world where “time to hire” is a key parameter for gaining traction in the recruitment firmament, sourcing cost is more often finding its place as a topic of discussion across many boardrooms.
HR process is ensconced with many repetitive processes which invariably lengthens the recruitment lifecycle resulting in a missed opportunity to hire the right fit for the role. Sniper AI, an AI, and Machine Learning-based sourcing and screening solution instill auto sourcing capabilities in the recruitment lifecycle by scanning and sourcing profiles from ATS and external databases like DICE, Monster based on job descriptions. The Machine Learning algorithms of Sniper AI, learn through every data set thus burnishing the accuracy level of finding the perfect candidate for the role, every time.
The qualification to success ratio pattern model, an upshot of a large sourced data of successful employees matches and grades the prospective employees against the job description matrix. The sourcing capability of SniperAI enables 37% sourcing cost reduction with smarter application management, effectively identifying potential candidates across existing data sources and reducing reliance on external clients.
The consistency of SniperAI in suggesting the “perfect fit” for the role candidate, eventually reduces a significant rehire cost which could have cropped up because of a wrong hire.
The Sniper AI’s, intelligent based platform, extract valuable information from various data sources and delivers best fit matches within seconds with utmost accuracy, thus reducing 53% of manpower doing administrative tasks associated with the hiring process. The easy % suitability comparison and availability of internal candidates will significantly reduce external agency spend.