OBJECTIVE AI MATCH SCORING ENGINE

Rank Candidates by Pure Merit and Requirement Fit

Score candidate relevance against required skills, tenure, education, and domain experience using unbiased semantic AI matching engines.

Test Match Scoring
✓ Verified Unbiased Semantic Matching Engine

NoticeScale AI Match Scoring Overview

AI Accuracy 98%
Sourced
24
Screened
12
Interviewed
6
Offered
2
SM
Sarah Miller
Senior Product Designer
FigmaDesign Systems
95%
Strong Fit
ML
Maria Lopez
Senior Frontend Engineer
ReactTypeScript
92%
Strong Fit
AI SHORTLIST MATCH
3 Top Qualified Candidates Ready
AI SPEED GAIN
10x Faster
Screening Workflow
01
Semantic Requirement Matching

High-Precision Semantic Requirement Matching

Evaluate candidates beyond exact keyword matches by understanding contextual skill relationships and domain experience.

Multi-layer document OCR & visual structure recognition
Automatic skill, education, & tenure standardization
Zero manual data entry workload for recruiter teams
Interactive Rubric Weighting StudioDynamic Recalculation
Tech Stack Weight50%
90% Adjusted Score
SM
Sarah Miller
Senior Product Designer
95% Fit
02
Customizable Rubric Weighting

Intelligent Customizable Rubric Weighting

Adjust weights for technical skills, experience duration, education, and must-have requirements for each job requisition.

Unbiased evaluation focused purely on verified merit
Customizable criteria per open job requisition
Real-time candidate profile insights and red flag detection
Unbiased Blind Screening Studio
Blind Mode
Role Technical Weight50%
AC
Alexandra Chen
Staff Frontend Architect · 8.5 Yrs Exp
98% Fit
SM
Sarah Miller
Senior Product Designer · 6.0 Yrs Exp
95% Fit
🛡️ 100% Bias-Free Evaluation Active — Evaluated strictly on verified merit
03
PII-Masked Blind Evaluation

Automated PII-Masked Blind Evaluation

Remove names, photos, gender, age, and location data to enforce 100% merit-based objective scoring.

Seamless integration with NoticeScale ATS pipeline
Empowers hiring managers with instant candidate insights
Reduces time-to-hire by over 50%
PII Masking & Merit Audit100% Unbiased
🛡️ Masked PII Audit Log:
• Full Name → Hidden (#CAND-9842)
• Profile Photo → Blurred
• Age & Gender → Omitted for Fairness
Merit Score
98% Fit
04
Detailed Match Fit Breakdown

Next-Generation Detailed Match Fit Breakdown

View granular scores for technical fit, tenure, salary expectation, and certification alignment.

Enterprise-grade encryption and GDPR privacy compliance
Protects employer brand with 100% communication rate
Detailed Match Fit BreakdownRadar Metrics
Tech Stack Fit99%
Experience Duration96%
Education Credentials95%
Alexandra Chen
Rank 1 Match (98%)

Key Measurable Benefits

Eliminate Unconscious Bias

Ensure fair, equitable candidate evaluation by scoring candidates strictly on job relevance and verified capabilities.

Instant Top 10% Identification

Focus recruiter interview capacity on high-probability candidates immediately after job post launch.

❓ FAQ

Frequently Asked Questions

Everything you need to know about our recruitment platform, features, and setup.

The match score evaluates candidates against your job requisition rubric, weighting hard skills, years of experience, education credentials, and mandatory knockout criteria.

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without manual reading?

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