← All work

Case study 01 · Recruitment & HR

AI Recruitment CRM

Resumes scored against the JD, every candidate in one pipeline, WhatsApp, email and voice follow-ups on autopilot.

  • Next.js
  • React
  • TypeScript
  • n8n
  • LLMs
  • WhatsApp API

The problem

Recruitment agencies pull candidate lists from LinkedIn and Naukri into Excel, read every resume by hand and chase each person over WhatsApp and phone. Nobody can see where a candidate stands, and follow-ups depend on memory.

What we built

  • A recruitment SaaS modelled on the best dialer-CRMs, with AI built into every step
  • Bulk CSV / resume import with AI parsing and a match score against the job description
  • Candidate pipeline, allocations, recurring follow-ups, calendar and call logs
  • Automatic WhatsApp and email outreach from templates
  • An AI voice agent that calls candidates to confirm interest and schedule interviews
  • Team live status and analytics for the agency owner

How it flows

From trigger to done, step by step.

  1. Resumes importedCSV, Naukri or LinkedIn export
  2. AI scores vs JDParsed and ranked in seconds
  3. Candidate pipelineAllocated to a recruiter
  4. WhatsApp + emailPersonalised outreach
  5. AI voice callConfirms interest, books slot
  6. Follow-upsUntil they reply or drop

What changed

  • ✓Every candidate tracked in one pipeline instead of scattered sheets
  • ✓Follow-ups sent by the system, not from memory
  • ✓Recruiters spend time on conversations, not data entry

Why it matters · industry benchmark

Manual screening is widely estimated at 12–18 hours per 100 resumes (industry estimate from recruiting-software vendors).

Source: Marxel, 2026

Live demo

See it inside Infinityy OS →

Your business

Build something like this →

Next case study

Clinic CRM with WhatsApp Inbox →