We don’t want to be cheeky, but using machine learning and AI is faster, cheaper, and better, in pretty much every possible way. Here’s what we mean:
Every recruiting “solution” on the resume filtering market involves forcing users to search through resumes by providing a list of specific set of keywords to find potential candidates to reach out to. This means that if you want to hire someone with a degree from a top university (say, UC Berkeley), you have to tell your recruiting software explicitly to find every resume in your system with a degree from UC Berkeley.
That, of course, is only a partial solution to your recruiting search problem. Searching for “UC Berkeley” will obviously give you a few great candidates, but you won’t see the candidates that are equally qualified from other great schools that you didn’t explicitly search for (like CalTech or Duke, for example). If you want to find those candidates, you’ll have to create scores of other searches, each naming a different top university, and hope you don’t forget to include any important university in your search.
Using recruiting software in this way can get a bit messy.
And the problem only gets more complicated when you want to isolate other important factors in your recruiting search, like a specific company in a candidate’s work history, or even just a job title, which can be incredibly difficult for keyword searching to differentiate. After all, just how many ways can people use different words to say “Software Engineer”?
Recruitbot is different because AI recruitment harnesses the power of machine learning to create solutions out of the problems described above. You don’t need to tell our AI recruiting software that UCBerkeley, CalTech and Duke are all top universities because it is able to utilize machine learning to determine candidates from top universities.
This is just one way that Recruitbot and our AI recruiting software can help save you time and find better candidates when searching for new potential employees.
