Screen job applications in seconds without losing the human signal
Sift extracts skills, experience, qualifications, and culture-fit signals from free-text job applications so hiring teams can shortlist faster and fairer.
The problem
Recruiters drown in applications. Each one requires manual reading, skill matching against the job spec, and data entry into the ATS. Top candidates slip through when volume overwhelms capacity. Unconscious bias creeps into manual screening.
The solution
Sift parses each application's free-text cover letter or response, extracts relevant skills, years of experience, qualifications, and standout factors, then scores the application against your job requirements. Recruiters review ranked shortlists, not piles.
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What users type
What you get
7 years — Senior Full-Stack Developer
React, Node.js, team leadership, 0-to-1 product builds
Led team of 4, seeking management track
4 weeks notice
Manchester, open to relocation
Why teams switch to Sift
10x faster screening
Structured extraction and scoring replaces manual reading. A 200-application pile becomes a ranked shortlist in minutes.
Consistent evaluation
Every application is scored against the same criteria. No variation based on which recruiter reviews it or when.
Surface hidden talent
Career changers and non-traditional backgrounds get fair evaluation based on actual skills, not just keyword matching.
ATS-ready output
Extracted data maps directly to ATS fields, eliminating manual data entry for every applicant.
The numbers
85% reduction
Screening time per role
AI-scored shortlists replace manual reading of every application cover letter and CV summary.
40% more
Qualified candidates surfaced
Structured analysis catches strong candidates that keyword-only screening would miss.
3 days faster
Time to first interview
Ranked shortlists enable same-day outreach to top candidates instead of week-long screening cycles.
Recommended fields
Recommended Form Fields
Frequently asked questions
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Use Cases
Sift extracts intent, budget signals, and urgency from free-text lead forms, then scores and enriches every submission so sales can prioritise instantly.
Client IntakeSift transforms free-text client intake submissions into structured profiles with goals, requirements, and red flags extracted automatically.
Incident ReportsSift extracts incident type, location, people involved, timeline, severity, and corrective actions from free-text incident reports for compliance and rapid response.