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Project
A business that connects job seekers and companies in real-time using AI.
Last updated: Oct 25, 2026
In the test environment, I confirmed that processing continues even after closing the screen when importing 100 job listings at once.
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Support Yu Kanda (Japanese)In recruitment services, a vast amount of manpower is used for job searching, proposals, recommendations, communication, and scheduling to connect job seekers and companies. As a result, companies pay high introduction fees, and recruitment agencies must continue to increase their career advisors (CAs) and recruitment advisors (RAs) to grow their sales. The aim is to reduce these intermediary tasks with AI and create a structure where people and jobs can connect more optimally and at lower costs.
An AI that understands job seekers and an AI that understands companies and job postings are connected, allowing only truly compatible combinations to meet naturally. The goal is to create a labor market where appropriate connections arise when needed, without the need for people to continually search through a large number of job postings or candidates.
We will start a paid pilot program with one recruitment agency that has a job placement license to verify how much we can streamline the process from "job search, proposal, to confirmation of application intent" using AI, utilizing actual job listings and job seekers.
First, we will target small to mid-sized recruitment agencies that have job introduction permits and job listings. Specifically, we will focus on companies where the number of Career Advisors (CAs) is limited, and they are unable to provide sufficient job proposals to all registered candidates.
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Candidates can now swipe through job listings and select "Interested," "Postponed," or "Wish to Apply," with the results being verifiable from the CA side. The person in charge of introductions has made progress in summarizing comparisons with current jobs, desired conditions, commuting time, and their connection to experience for each job listing.
On the job seeker side, we have summarized the profile display and improved the response to screen transitions and swipes. Using fictitious candidates and job listings, we generated three personalized proposals with AI, separating the explanations for candidates and the confirmation items for the introducer. Integration of the proposals into the screen has not yet been completed, and actual candidate information has not been provided to the AI.
I have progressed to the point where I can actually interact with the beta version on my iPhone. Upon using it, I realized that it requires too much input and confirmation from the candidate side, making the process of viewing job listings cumbersome. Moving forward, we will change the flow so that the CA pre-enters candidate information, allowing candidates to view job listings immediately after logging in.
R. decided to move forward by releasing a free beta version instead of introducing the product to companies one by one through sales, allowing the product's quality to naturally replace existing systems. The input platform, which enables career advisors and job seekers to create candidates, register documents, add job listings, input preferences, and log in via a browser, has reached the testing screen. However, during practical verification, it was found that issues such as screen transition delays, slow document and job importation, and the difficulty in using automatic transcription and preference input still remain.
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R. is advancing its policy as a system provided to recruitment agencies with employment introduction permits. It has progressed to an operational flow where job seekers can swipe through job listings, and career advisors can review and determine matches. We have confirmed connections to Supabase, candidate segregation through dedicated URLs, saving swipe results, and the separation of stated preferences, work history basis, and inferred tendencies from behavior in the actual database. Furthermore, we have also confirmed a route to retrieve job information from the job listing URLs shared with candidates, allowing for incorporation into the existing job data without duplication.
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