> No black-box AI. Every candidate gets a detailed match receipt explaining exactly why they scored an 85%, complete with contextual evidence from their CV.
HR teams like to play dead when they actually have a file with detailed feedback on a candidate. Yet, they choose to keep that to themselves out of baseless legal fear. I wonder how that works out when somebody proves a company's filter consistently proves a specific bias gets rejected systematically.
and
> Automated assignment validation
which is particularly troubling for devs: companies scaling assignments as first screen. How do you get around "AI evaluating AI" loops especially about assignments ?
In our software, the candidate being assessed does not know all the assessment criteria. Furthermore, this assessment is merely a starting point for discussion during the technical round. I need to update the description of this feature.
Thanks for the valid points!
How do you deal with CVs like mine that refuse to list every <fancy keyword> I'm familiar with because it's pointless clutter? In that sense, and IME, the companies that only hire perfect fits are, more often than not, toxic.
I like the landing page.
So I am wondering what kind of tooling would be able to somehow spot the right people among flood of AI slops.
also matching requirements should be secondary to experience. someone who has done a few react websites will not be as qualified for your react job as someone that has done 10 years of angular and vue and can learn react in a short time.