Six modules. One pipeline.
Each module ships standalone — together they form a fully governed Recruitment Intelligence System.
CV Parsing
Multi-format parsing tuned for African templates. Skills, experience, education — structured in seconds.
Intelligent Screening
Multi-dimensional fit scoring across role-fit, aptitude, experience and culture. Auditable end-to-end.
AI Recommendations
Smart rankings + cross-role matching. Strong-but-wrong-fit candidates auto-redirected to better roles.
Adaptive Interview
AI-led, branching interviews scored on STAR, communication, and confidence — with full transcripts.
Continuous Scoring
Pipeline-wide scoring with weighted CV / application / assessment / interview blending.
Ethical Governance
Bias monitoring, fairness reports, and human-in-the-loop overrides on every decision.
Built for hiring teams that care
Equity, transparency, and explainability are first-class features — not afterthoughts.
See your shortlist ranked, not just listed
Every candidate is scored across four weighted dimensions — CV fit, application quality, assessment performance, and interview signal. Adjust the weights, and the ranking recomputes in real time. No black boxes — every score is auditable.
| Candidate | ||||
|---|---|---|---|---|
Aisha Bello Senior Backend Eng | 94% | 92 | 96 | 95 |
Tariq Mensah Senior Backend Eng | 89% | 88 | 91 | 87 |
Naledi Khumalo Senior Backend Eng | 85% | 81 | 90 | 84 |
James Okafor Senior Backend Eng | 78% | 84 | 72 | 79 |
Lerato Dlamini Senior Backend Eng | 71% | 68 | 74 | 72 |
Real-world scenarios, scored as they answer
Every interview is scenario-based — the AI throws a realistic situation the candidate would actually face on the job, then scores their judgment, decisions, and action plan in real time. Branching follow-ups adapt to what they say, and you ship out with a full transcript and PDF.
Scenario: It's Friday afternoon. A senior engineer just merged a change that broke checkout for 8% of users in production. Your PM is asking for an ETA, support tickets are spiking, and the engineer who shipped it is offline. What do you do in the first 30 minutes?
First, stop the bleeding — roll back or feature-flag the change before triaging root cause. I'd post a single status thread so PM, support, and on-call see one source of truth, then pair with whoever is closest to the code to reproduce. The offline engineer can be looped in async with a clean writeup.
Good — now the rollback fails because of a database migration that already ran. How does your plan change?