AI screening for engineering roles
Keyword filters miss good engineers who describe their stack in non-obvious ways. The Scorify uses semantic AI scoring — a candidate who built "distributed pipelines on Kafka" matches a job that asks for "event-streaming experience."
Tech hiring realities
200 applicants per engineering role, most don't match the stack
Keyword filters kill good candidates with non-obvious resumes
No time to generate fresh technical questions per candidate
Non-technical recruiters can't pre-screen well, engineers get swamped
Why semantic scoring beats keyword filters
Boolean ATS filters ("must contain: Python AND React") produce a brittle pipeline — you miss the Ruby engineer who'd crush Python in week two, or the React Native dev whose resume doesn't say "React." The Scorify reads each CV in context, matching skills and experience against your job description by meaning, not string overlap. Good candidates stop getting filtered out.
What engineering leads get
- Semantic skill matching — not just keyword AND/OR
- Customizable weights: seniority, must-haves, nice-to-haves
- AI-generated technical questions tailored per candidate
- Bulk upload — drop 200 CVs as a ZIP, get ranked list in ~90s
- Non-technical recruiters can run first-pass screening confidently