An AI system scores candidates by extracting data from their profiles—employers, years of experience, job-switching patterns—and answering yes-or-no questions about fit. Each match earns points that add up to a lead score, letting recruiters filter candidates faster.
What this will do is enrich their personal profile and bring in their summary. Of course, not everyone has a summary, but there's a lot of data you can pull from their profile. So it might be like their previous employers, their total years of experience, how quick they move between jobs. You might have a company that says, we won't hire someone that has moved within 6 months of joining a role. What we can then do is feed all that data to AI, say, has this person moved jobs within 6 months? AI will look at their profile and reply with a yes or no. We then add another thing to say, do they mention Voice over IP on their profile as a technology? AI looks at their summary. If it doesn't mention Voice over IP, replies with a no. And then we get points for each criteria they do or do not have, and we add that up. And that's the lead scoring process that we can use to actually filter out candidates and do sourcing through this platform.
