Recruitment operations
AI Candidate Intake and Shortlisting System
Automates candidate intake and first-pass review for businesses handling frequent hiring, high applicant volumes, and repeated screening workflows.
Business outcome
Reduce manual applicant screening and speed up hiring response times while keeping human approval and auditability in the process.
Use case fit
Best fit for businesses that handle frequent hiring, high applicant volumes, or repeated candidate screening across multiple roles. Useful for recruitment agencies, care providers, hospitality groups, logistics teams, retail operators, and other organisations where hiring workflows create significant operational admin.
Operational workflow
The workflow diagram shows how the automation moves work from intake to review, downstream updates, and auditability.
Reference architecture
The architecture view uses neutral system blocks to show data flow, integration boundaries, review points, and operational logging.
Sources
Candidate sources
Email, form, job board, LinkedIn export
Automation core
Intake UI
Candidate profile capture and role selection
AI scoring layer
Fit score, summary, matched skills, gaps
Recruiter dashboard
Shortlist, reject, or request more information
Integrations
ATS/CRM connector
Candidate status, notes, pipeline updates
Notification layer
Recruiter alerts through email, Slack, or Teams
Governance
Audit log
Traceable automation and human-review events
Technical stack
- Next.js
- TypeScript
- Tailwind CSS
- Mocked AI scoring
- OpenAI-ready API layer
- ATS/CRM integration path
Integration path
- CV parsing
- OpenAI evaluation route
- Postgres or Supabase storage
- Bullhorn, Greenhouse, Lever, HubSpot, or Zoho Recruit
- Email, Slack, or Teams notifications
Implementation notes
- The public demo uses mocked AI to keep walkthroughs stable.
- A production build can replace the mock layer with a real model and role-specific scoring rules.
- The architecture keeps recruiters responsible for final decisions.