Utilizing AI in Talent Acquisition to Build a SAAS Platform

Our client was one of the first European HR and Recruiting market players that not only understood the endless potential of IT for this specific market niche but also introduced a digital solution that brought actual value to businesses and showed how to incorporate AI in talent acquisition. Our client’s platform simplified and supported multiple talent acquisition and recruiting processes allowing the companies to hire new employees faster and easier. However, due to the rapid development of the IT sector, technology and software development strategies that were relevant in 2012 became dated pretty quickly. As time passed, this factor began to negatively influence the software’s performance and our client’s opportunities for business growth. Consequently, they required assistance from an experienced tech team that had several HR and Recruiting projects under their belt and was able to update and improve the existing system.

Introducing a transparent streamlined work process was the first step toward resolving the existing challenges. It helped achieve visible results in a shorter amount of time and provide consistent delivery without risk to the existing software. The project required high proficiency in Big Data, Machine Learning, Python, Django, PostgreSQL, Cassandra, and RabbitMQ, plus data mining and AI in talent acquisition to bring the complex functionality of the platform to the next level. Light IT Global’s development team has successfully ported the existing code from Python 2 to Python 3, as many of the repositories required the update. At the same time, the team has created several tools that improved the data processing speed. The microservices development boosted the data processing speed and enhanced the quality of the matching algorithm. One of the newly-developed elements took on the role of the mediator between the service and the application. That specific microservice carried the data flow and helped shortlist the candidates/talents according to the established parameters. As a result, the matching algorithm that brings the power of AI in talent acquisition was able to provide a recruiter with high-quality candidates that meet the requirements 100%. The introduction of Elasticsearch made the matching algorithm even more effective and truly unleashed the potential of AI for talent acquisition. The system started to analyze significant volumes of data faster and give back answers in milliseconds. An innovative combination of Machine Learning, Big Data, natural language processing, and AI for talent acquisition ensured the seamless operation of the whole system. Several additional web pages were developed to guarantee a smooth workflow and better user experience. Hence, the solution finally started to live up to its potential. The new functionality was thoroughly tested to ensure the highest quality of the freshly introduced solutions and 100% compatibility with the existing components.

A revamped talent acquisition platform was based on microservices architecture, which safeguarded better scalability, flexibility, and stability for an entire system. The new microservices can be easily added per the business owner’s request at any time. Multiple teams can implement new features simultaneously. And even technical issues with one of the microservices will not lead to the failure of the whole system as it was earlier when the platform was based on monolithic architecture. After the introduction of new functionality, a unique matching algorithm, which is our client’s trademark and uses the power of AI for talent acquisition, became more precise and quick. It now helps businesses find employees that meet even the most strict requirements and makes it easier for candidates to find a job that is perfect for them. Another important aspect is a noticeable boost in the system’s performance. For example, the data processing speed increased by 50%, the customer requests are now taken care of in a matter of seconds. A 65% downtime reduction and a 35% improvement of the code maintenance speed were achieved as well. As a result, the improved fault isolation, minimized downtime rate, increased data processing, and code maintenance speed boosted overall efficiency and nurtured customer satisfaction.

Once the new functionality was successfully implemented and passed the QA, the platform became more efficient and easy to use. The matching algorithm became sharper and more precise, leading to a noticeable boost in customer satisfaction. The revamped platform can serve more clients without the risk of a downturn in the business cycle. Improved technical flexibility allows our client cut costs related to software development and the system’s maintenance, as the platform is no longer bound to a specific tech stack because microservices can be developed in different programming languages. A major improvement in data processing speed and download rate allowed the system to cope with the higher system load and cater to a larger audience.