Project
About project
About project
About project
When faced with a high volume of applications, HR teams are forced to spend many working hours manually reviewing resumes. As a result, hiring speed slows down and strong candidates can get lost in the crowd. Doubletapp’s ML unit implemented an AI assistant that automatically ranks applications for open positions, allowing recruiters to work only with relevant candidates. After introducing the AI assistant into its hiring processes, Doubletapp increased HR department efficiency by 40%.
The AI Recruitment Tool helps HR teams handling large volumes of applications centrally manage vacancies and candidate resumes, automatically filter out irrelevant applications, and make hiring decisions faster.
Business Challenge
Business Challenge
Business Challenge
For popular roles, recruiters receive hundreds of applications. Due to the large number of irrelevant submissions, HR specialists are overloaded with routine manual work: they spend excessive time reviewing resumes, fail to respond quickly, and risk losing strong candidates. This directly affects time-to-hire and overall hiring quality.
For example, we posted a backend developer vacancy on a popular job search platform and received around a hundred applications. More than half of the candidates lacked the required skills, experience, or education and were simply trying to “break into IT quickly.” As a result, by the time we identified a truly strong candidate and began negotiations, they had already accepted an offer from another company.
The goal of our HR service is to prevent such situations by ensuring fast and accurate resume processing, accelerating hiring cycles, and helping companies remain competitive by attracting top talent.
Solution
Solution
Solution
We developed a service with intelligent ranking and transparent candidate evaluation logic. Let’s look at the service interface:
1. Applications Page
The main screen displays all applications for a vacancy and immediately shows each candidate’s match score against the requirements. Candidates are ranked by relevance, and recruiters can add candidates to favorites or reject them.
2. Candidate Profile Page
Each candidate has a detailed profile: on the left is the automatically imported resume, and on the right is the AI analysis with a concise summary and a skills assessment mapped to the vacancy requirements.
3. Requirements Checklist
A structured checklist is automatically generated from the job description, making it easy to evaluate candidates. HR managers can apply additional filters, and the system instantly re-sorts candidates based on the new criteria. The checklist translates the job description into a clear system of criteria, reducing subjectivity in evaluation.
4. Company Vacancies
All vacancies are automatically pulled from job search platforms. They can be conveniently filtered by status (active or archived), responsible managers, and publication date.
As a result, HR no longer manually sorts through streams of resumes but works with already structured and prioritized data.
Results
Results
Results
After implementing the service:
- HR department efficiency increased by 40% thanks to automated processing of large volumes of resumes.
- Application review speed improved: the system analyzes over 5,000 candidate profiles and immediately presents a clear, easy-to-understand ranking.
- The risk of errors decreased: each candidate is evaluated against clear parameters, and the requirements checklist allows HR teams to control selection quality and adjust criteria when needed.
- The hiring process became transparent and manageable: a report is generated for each candidate, highlighting skills that match and do not match the vacancy.
Automating application processing enabled HR teams to focus on relevant candidates, reduce time spent on initial screening, and minimize errors through unified evaluation criteria. The result: vacancies are filled faster, teams spend fewer resources on routine tasks, and hiring quality improves.
