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Human Resources

Recruitment team automates CV screening with AI scoring

Recruiters were posting to each job portal by hand and reading every CV one by one. We built them an internal Talent Intelligence Workspace that posts everywhere at once, reads every CV with AI, scores candidates against weights the recruiters control, and keeps every profile searchable for the next opening.

What we used: AI & Machine Learning, Intelligent Document Processing, Process Automation

End-to-end flow of the recruitment automation, from job posting to ranked candidates
The end-to-end flow — from job posting to ranked candidates.

1The problem

  • Every job had to be created, posted, and tracked separately on each job portal, across multiple regions.
  • CVs arrived from many channels; recruiters opened and read each one manually, portal by portal.
  • Screening at high volume depended on individual judgement — strong candidates could sit unread in the pile.
  • Once a hiring round ended, past candidates’ CVs were effectively lost, buried across portal accounts and inboxes.

2What we did

  1. 1An internal Talent Intelligence Workspace for the recruitment team, with user credentials managed in-house for security.
  2. 2Automation drafts and posts jobs across portals and collects applicants into one place; a dashboard flags drafts, posting failures, exceptions, and new CVs since the last login.
  3. 3AI reads each CV and normalizes it into a structured profile — personal details, skills, work history, education, and certifications.
  4. 4Recruiters tune the scoring weights per job — skills and experience relevance, education and qualifications, overall fit — with the categories always totalling 100%.
  5. 5Every profile carries an AI summary: breakdown scores per category, strengths and weaknesses against the job description, and suggested interview questions.
  6. 6Recruiters compare top candidates side by side and download original CVs in bulk — without logging into any job board.
  7. 7All historical profiles flow into one searchable talent database, with boolean search across skills, certifications, and years of experience, covering candidates from Hong Kong, China, Singapore, and Malaysia.

3Inside the Platform

Workspace dashboard with status cards for drafts, posting failures, new CVs, and posted jobs
The dashboard tracks postings, flags automation exceptions needing attention, and shows new CVs since the last login.
Unified job list showing multi-region requisitions with per-portal status
Multi-region job requisitions consolidated in one list, with live status and last-updated time per portal.
Scoring weight configuration with three categories totalling 100 percent
Recruiters tune the AI scoring weights for each job — the categories always total 100%.
Job details view with structured requirements used for candidate matching
Job details held as structured data that drives the matching and scoring.
Candidate list aggregated from multiple portals, ranked by AI score
Candidates aggregated from every portal, ranked by AI score — separated by source, scored on the same criteria.
CV extraction view turning a CV into structured sections with AI analysis
Each CV becomes a structured profile: details, skills, work history, education, certifications — plus an AI summary with strengths, weaknesses, and suggested interview questions.
Candidate profile with recruiter remarks and original CV download links
Recruiters add live remarks and statuses, and download original CVs without visiting the job boards.
Side-by-side comparison of selected candidates with scores and AI summaries
Top candidates compared side by side — scores, AI summaries, and credentials in a single view.
Boolean talent search across the historical candidate database
Boolean search across the historical talent database — skills, certifications, years of experience — so past candidates surface instantly for new roles.

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