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The AI Job Application Screener is an advanced tool that uses artificial intelligence to analyze resumes and generate insightful summaries of applicants' qualifications. It makes the job application screening process more efficient as it systematically organizes and presents the candidates' qualifications, prioritizing those that best match the requirements of the available job position.

The AI Job Application Screener works by leveraging artificial intelligence to review and analyze job applications. It creates summaries of the applicants' qualifications which are then organized and ranked in order of relevance and suitability for the job. This advanced tool also enables bias removal by modifying identifiers into initials and excluding potential bias indicators, such as graduation years. Additionally, it offers the feature to describe an ideal candidate against which applicant stacks can be re-ranked.

The AI Job Application Screener offers several impactful features. It enables defining an ideal candidate to find a perfect match, and it allows recruiters to upload a top employee's resume to find similar applicants. It has an instant bias removal feature, which maintains fairness by turning names into initials and excluding graduation years. The AI Job Application Screener also facilitates faster decision-making through its keyboard hotkeys, enabling advance, hold, advance decisions with minimal clicks.

The creators of the AI Job Application Screener are software engineering professionals hailing from LinkedIn, Apple, and Y Combinator. Having vast experience in recruiting and software engineering, they have developed this AI-based tool to enhance the efficiency of job application screening.

The AI Job Application Screener is compatible with several Applicant Tracking Systems (ATS), including Ashby, Cornerstone, Greenhouse, ICIMS, Indeed, JazzHR, Jobvite, Lever, SAP Success Factors, Smart Recruiters, TalentReef, Taleo, Workable, and Workday. This array of ATS integrations ensures a bi-directional data synchronization, keeping all decisions updated in your existing system.

The AI Job Application Screener employs several methods to reduce bias in recruitment. It transforms names into initials and removes graduation years, hence nullifying the influence of gender, race, and age. This feature ensures the decision-making process stays unbiased and solely focused on candidate suitability for the role.

The AI Job Application Screener has a pricing model based on usage. During its closed-beta phase, it can be accessed for a one-time payment of $250, providing unlimited access for one user for all of 2023. After its public release in October 2023, it transitions to a per-user monthly pricing scheme of $200, offering unlimited jobs and applications, support, and a no-contract, month-to-month arrangement.

You can gain early access to the AI Job Application Screener by paying a one-time fee of $250. This will provide unlimited access for one user for the entirety of 2023. This fee is fully refundable, and early access also enables guide roadmap priority.

The AI Job Application Screener presents customizable options via a Software Development Kit (SDK). Using the SDK, the tool can be tailored for both internal or user-facing scenarios, providing the headless UI for custom white-labeled design in a pay-per-use model.

The AI Job Application Screener will be publicly released in October 2023.

AI-written summaries of applicants' qualifications are generated by the AI Job Application Screener to condense the information on the resumes and highlight critical aspects of the applicant's experiences and qualifications. This makes the reviewing process more efficient and allows recruiters to quickly assess the potential fit of the applicant for the job.

The AI Job Application Screener ranks job applicants by using AI algorithms to match their qualifications, experience, skills, and other relevant attributes to the job requirement. It then ranks the applicants based on the best fit, highlighting mismatches and allowing recruiters to focus on primary candidate suitability.

Yes, the AI Job Application Screener offers the functionality where recruiters can upload a top employee's resume. The AI then sorts applicants based on similarity to this reference resume in order to find 'clones' among the applicants.

With the AI Job Application Screener, you can describe your ideal candidate by entering desired traits and qualifications. The tool will then re-rank the application stack based on the similarity to these desired characteristics, highlighting these traits in green for quick recognition.

After the closed beta of the AI Job Application Screener concludes on August 25th, 2023, the public release of the tool is scheduled for October 2023. Until then, early access to the product is available for a one-time payment of $250.

While the website doesn't explicitly detail how to directly contact the team behind the AI Job Application Screener, they do offer a 'Contact Us' prompt presumably to address inquiries about their platform plan and SDK integration.

Yes, the AI Job Application Screener does offer a per-user monthly pricing. After its public release in October 2023, the pricing would be $200 per user per month, which includes unlimited jobs and applications, access to a polished production product, and 24/7 support from the founders.

The SDK offered by AI Job Application Screener provides a multitude of customization options. It enables the tool's integration for internal or user-facing scenarios, allowing a headless UI for custom white-labeled design on a pay-per-use model.

The AI Job Application Screener sorts through applications by harnessing artificial intelligence to scrutinize resumes and produce insightful summaries of the applicants' qualifications. It then categorizes these summaries in an unbiased sequence, positioning those candidates that best match the job requirement at the top of the list.

Yes, with the AI Job Application Screener, you can prioritize your preferred candidate traits. By outlining these traits, the tool will re-rank the applicants' stack based on the similarity to these desired characteristics. Such traits will be called out in green, significantly assisting in zeroing in on the most fitting applicants.