Attention HR Recruiters, Hiring Managers and Agencies
Fill tech roles 3× faster —without hours of manual screening or irrelevant profiles
AI Talent Acceleration System (ATAS) shortlists top candidates in under 60 seconds, replaces manual screening, and — if your hiring speed doesn’t improve in 30 days, you don’t pay for the next month.
Watch a walk-through showing how ATAS finds, evaluates and schedules the right candidates — automatically.
→ Why most tech hiring funnels are full of irrelevant profiles
→ How ATAS uses JD to extract skills and uses multi-source sourcing to find real talent.
→ The exact steps we use to eliminate interview wastage and reduce ghosting.
Trusted by Companies and Agencies
Sick of screening thousands of irrelevant resumes, late joins and offer dropouts?
Screening resumes takes hours and yields low-quality shortlists.
Hard-to-fill niche tech roles produce long hiring cycles.
Managers frustrated with poor quality interviews & subjective feedback.
A faster, better, cheaper hiring pipeline —
guaranteed
Fill roles 3× faster using AI screening, evaluation & predictive scoring
Shortlist relevant candidates in under 60 seconds
Reduce interview wastage and offer-dropouts by up to 40%
If hiring speed does not increase within 30 days after onboarding, you don’t pay for the next month.
How ATAS Works
Phase 1 — Talent Discovery
• JD → skill extraction, inbound parsing, multi-source outbound discovery
• One-click shortlisting & candidate ranking
Phase 2 — AI Evaluation
• Domain micro-tests, AI Technical Interviewer, skill-gap detection
• Ghosting & offer-dropout prediction, compensation alignment
Phase 3 — Hiring Ops Automation
• Interview scheduling, calendar sync, automated comms & documentation
• Pipeline dashboard, bottleneck identification & predictive risk scoring
Case Studies
Immigrant Networks
Before:
4-week average to shortlist; 60% interview wastage.
After:
Shortlisted top 20% in less than a day ; 3× faster time-to-offer in 30 days.
Result: Reduced candidate shortlisting time by 70%
AVL
Before:
High offer-dropouts for mid-senior backend roles.
After:
Behaviour prediction & compensation alignment reduced dropouts by 35%.
Result: Improved candidate dropout rate by 28%
World of Tee
Before:
Manual scheduling caused long delays in hiring