Overview
Recruiters were bottlenecked by manual CV review and repetitive follow-up preparation. The product required a full rebuild to stay competitive.
The challenge
The platform needed to support multilingual intake, high screening throughput, and transparent oversight for AI-assisted hiring decisions.
Our approach
We delivered an end-to-end ATS rebuild with private model inference, smart candidate questioning, and confidence-based manual review paths.
What we delivered
- •Private AI scoring pipeline with role-aware prompts
- •Smart Questions module for targeted interviews
- •Subscription and billing integration
- •Operational dashboard and monitoring setup
Architecture and implementation
- •Kubernetes-based deployment for load elasticity
- •Scoring confidence thresholds for mandatory human review
- •Separate services for ingestion, scoring, and recruiter experience
Delivery timeline
Month 1
Scope and architecture
Defined product boundaries and data flow for an AI-first ATS.
Month 2
Core build
Implemented scoring, ranking, smart questions, and recruiter panels.
Month 3
Launch readiness
Completed hardening, controls, and commercial rollout support.
Screens and artifacts
Screening throughput per recruiter
Technology
Compliance and controls
- Human review path for low-confidence outputs
- Private processing path for candidate data
- Documented controls aligned with recruitment governance expectations
Key outcomes
- ✓Recruiter workflow shifted from manual scanning to guided decision support
- ✓Candidate evaluation consistency improved through structured scoring
- ✓Product launched with enterprise-ready architecture
Related case studies
This case study is shown at a summary level due to NDA. Full technical detail and references are available on request. Some model governance documents and client-specific thresholds are omitted. Contact us.