Job Agency System

Resumes once lived across Excel, WhatsApp, WeChat, email inboxes and paper files; matching relied on senior consultants' personal experience, so service quality wobbled whenever the team grew.

Imported-labour posts carry many hard requirements — certificates, language, experience — and manual screening misses them; imprecise referrals directly erode employer trust.

Mainland-side resumes are plentiful but scattered across channels; Macao-side employer demand arrives through personal connections and lags, so competitors hear about new demand first.

Hospitality roles turn over fast and need constant backfill; resumes are used once and lost; departmental requests arrive by email and word of mouth, so HR repeats the same screening and channel costs stay high.

Each Hong Kong talent scheme — TTPS, QMAS, ASMTP — sets different education, income and experience thresholds, making manual eligibility checks slow; when a policy window opens, resume volume surges beyond what manual screening can absorb.

Candidate resumes mix Chinese and English in inconsistent formats; senior-role criteria are implicit and matching relies on individual judgment; high-end candidates sit dormant in contact lists for years.

Factory hiring comes in peaks; client relationships and matching know-how sit with individuals, so a senior consultant's exit means starting over — headcount grows while per-capita output falls.

Resumes scatter across 58.com, BOSS Zhipin and WeChat groups in messy formats; consultants hunt through chat history; the company owns no reusable talent asset.

Communities, sub-district offices and employment bases are tasked with referring jobs to local residents — a large service population with widely varying skills; job and job-seeker information sits in spreadsheets and ledgers, so manual matching is slow and referral precision is hard to improve.

A resume library of 100k+ built over years is the core asset; a consultant team of dozens needs tiered data permissions; policy requires all resume and business data to stay on company servers.

Two or three consultants, no dedicated IT, limited budget, ordinary office hardware; the fear is a system that is complex to launch and costly to maintain.

The group already runs self-built CRM and business systems that cannot be replaced; it lacks AI resume parsing and matching, which are costly and slow to build in-house, and data must stay inside its own environment.