We’ve been researching and implementing ways to make your candidate database not only easily accessible and searchable, but a living, responsive pool of potential applicants for the jobs that you’re working on.
When we started building Connect, we created a comprehensive search capability along with applicant tags, Boolean keywords, and other relatively intuitive ways to search. We leverage true lexical parsing of resumes into intelligent taxonomies that could later be easily organized and searched upon. This is available today within our intuitive search interface to make it as easy as possible to enter search criteria via our “Google-esque” search bar. Today, we feel strongly that we offer the best talent search capability on the market.
A trained recruiter can go into Avionté and narrow down their candidate population to the exact subset they are looking for based on keywords in a resume, education/work/activity history, text in email conversations, and countless other search variables.
While monitoring how users engaged with these tools, we started noticing patterns in the way searches were run. We saw very effective search patterns that lead to placements and revenue, as well as patterns that lead to lost positions.
It was at this juncture that we realized that we could train a machine to think and search for talent like a seasoned recruiter and thus enable a junior level recruiter to perform at levels much more experienced. We’ve found this technology to be extremely beneficial within the clerical light industrial, professional and technology sectors of recruiting.
We’ve since embarked on Avionté TI, utilizing machine learning and artificial intelligence. Through TI, we’ve started with “Talent Compare”. By creating deep learning models of your entire database, we’ve found that it can answer some very complex questions. Rather than needing to search for candidates in your database, Talent Compare will show candidates that compare to any candidate profile.
For example with Talent Compare:
“Often times a recruiter needs to find candidates who are like one they’ve worked with in the past or are currently working with. Given this particular candidate with his / her skills and experience – Talent Compare shows others that may have similar traits and happen to live around the same area.” This is done in real time within each candidate profile, but also within Talent Search so a user can filter by additional criteria and/or take mass actions. The algorithm is further tuned by including other interactive training factors such as personal contact history and previous job history with your agency. With an almost unlimited number of dimensions and vectors available to the data, the algorithm is trained and gets better over time.
Using the same technology, we can also give accurate results for Talent to Jobs, and Jobs to Talent. We’re the only platform that has been adventurous enough to tackle this, and our initial results since we have released our first phase have been very promising. Talent to Jobs exists in the candidate profile and will pull up jobs that are open within your database that it thinks the candidate should be considered for. Jobs to Talent resides within the Talent view of a job where it will show candidates that may qualify for that job.
Future enhancements will include candidate profile enrichment and auto updates to further feed into the AI model which will continue to grow the algorithm and increase the quality and complexity of the answers retrieved.
We’re striving to make the platform more responsive and alive rather than just a static database. Your system does not rest, take breaks, sleep or take vacations. It should always be working to find you the best talent available to fill positions.
About Avionté
Avionté is a leader in enterprise staffing and recruiting software solutions, offering innovative end-to-end staffing solutions to over 900 customers and 25,000 users throughout the U.S. and Canada. Avionté delivers a robust platform for clerical, light industrial, IT and professional staffing firms to maximize profits and boost productivity.
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