Semantic Matching

Explainable matching recruiters can trust and defend.

Score and rank candidates against role requirements with transparent signals hiring managers and compliance teams can audit.

Explainable AI

Visible skill overlap signals

Configurable Rules

Weights by role type

Semantic match scores

Candidate 192%
Candidate 287%
Candidate 381%

Why semantic matching

Traditional ATS search vs. InsyghtAI

Capability
Traditional
InsyghtAI
Keyword-only search
Limited
Semantic intent
Match transparency
Black box
Explainable scores
Skill adjacency
Manual
AI-expanded clusters
HM trust
Low
Audit-ready exports

How semantic matching works

From requisition requirements to ranked, explainable shortlists.

Step 01

Parse

Extract skill requirements and context from requisition data.

Step 02

Compare

Semantic analysis of resumes against role requirements.

Step 03

Score

Generate weighted scores with visible overlap signals.

Step 04

Review

Recruiters validate, provide feedback, and refine rankings.

98% Match Quality

On validated shortlists

Audit-Ready

Explainability exports

Fewer False Positives

Higher shortlist precision

HM Alignment

Shared match language

Feedback Learning

Improves over time

InsyghtAI Hub

HRIS
Compliance
CRM
Payroll
Data
BI
SSO

Integrations

Embedded in your hiring workflow

Matching scores appear at search, pipeline, and copilot touchpoints.

SearchPipelineCopilotReportsAPIAudit

Score API

Feedback Loops

Custom Weights

Export Logs

Why InsyghtAI

Built for enterprise outcomes—not experiments

InsyghtAI delivers semantic matching with visible skill overlap, gap analysis, and configurable ranking weights by role type.

Higher shortlist quality with fewer false positives

Audit-friendly match explanations for enterprise governance

Faster consensus between recruiters and hiring managers

Ready for matching your team can trust?

See explainable semantic matching in a demo with your role types and requirements.