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Beamery AI Explained
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Technologies like artificial intelligence (AI) are powerful tools recruiters can use to sift through large amounts of data. It can enable them to interpret resumes better as well as suggest better candidate matches. For the candidate, AI can lead to greater personalization. It can surface higher quality matches, thus streamlining the job seeking experience and highlighting internal and external opportunities with greater relevance. Click here to learn about the fundamentals of AI in Talent Management and Acquisition. 

Beamery helps recruiters identify, source, and engage candidates with the right skills and potential for success within the organization. It also serves to help recruiters find engaged talent faster and reduce hiring times. 
To achieve that, Beamery uses AI in a few key ways:

AI Matching with Explainability
Suggested Contacts
Transparency with Explainability

AI Matching with Explainability

As the volume of candidates and talent increases it becomes more challenging to track. We help Sourcers and Recruiters find and evaluate candidates based on their skills and potential. To do that, Beamery’s AI Matching helps our customers to see inbound applicants scored against what hiring managers are looking for – giving hiring teams a streamlined, consistent view of fit and saving them time by focusing on quality candidates first.

Suggested Contacts

Beamery’s AI-powered Suggested Contacts feature uses frequency matching on key attributes to find relevant contacts for Sourcers and Recruiters to add to Pools, finding the closest fits for their ideal candidate profile. Suggested Contacts helps reduce the time to hire with suggested contacts or resurfaced contacts, with prioritized explainability to help you make fast decisions, understanding not just who’s a fit, but why the system suggested these candidates for review. We further empower our users to, in turn, explain recommendations and decisions to candidates.

Transparency with Explainability

Beamery helps you understand why we predict that someone will be a good match for a role, using a few key explanation layers, which can be provided to candidates, that clarify the AI  recommendation.

  • See each component’s weight (or influence) in the decision: our AI recommendations articulate what is the mix and weight of skills, seniority, proficiency and industry, so you can clearly see the main reason our AI considered a potential fit between talent and vacancies.
  • Understand what skills impacted the recommendations the most, and what skills did or did not have an impact on the recommendation.