AI & Data
Semantic AI matching that connects job seekers with the companies that need their skills.
- Client
- HAND (Human Aid & Development)
- Sector
- NGO · Employment · AI matching
- Market
- Syria
- Platforms
- Web app (PWA) · Company portals · Admin console
- Technology
- Next.js 16Firebase AuthFirestore vector searchCloud FunctionsVertex AIFCMApp CheckApp Hosting
Overview
Jahez to Work (جاهز للعمل) is HAND’s skills-to-work platform. Job seekers build verified profiles, companies get their own portals to post offers, and an AI matching engine ranks candidates by meaning, not keywords, with the evidence behind every score. HAND operators verify documents, follow up after placement and track the outcomes that matter through seven built-in indicators. A dedicated Events module handles QR attendance and feedback.
7
Outcome KPIs tracked
3
Portals: seeker, company, HAND
0
Keyword rules: matching is semantic
What we built
Semantic matching with Vertex AI embeddings and Firestore vector search, plus hard filters (e.g. freelancers never matched to full-time roles)
Ranked candidates with transparent evidence for every match score
Company portals: profile, documents, job offers with expiry and work type, private ratings
Operator verification queue for ID and clean-record documents, then scheduled follow-ups at 1/3/6/12 months
Seven KPIs on the HAND console: interviews, placements, promotions, raises, switches and category gaps
Events module: QR attendance, 5-star feedback and custom questions per event
QR codes on every profile and offer: scan a seeker at a job fair to star them instantly
Arabic-first bilingual UI, push notifications via FCM, Excel import/export
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