Search Recruitment Data with an Evidence-Backed AI Assistant

Candidate and job data ingestion

Create a Searchable Recruitment Knowledge Base

Candidate résumés, job descriptions, interview notes, skills, experience, and application history can be processed and organized into a shared search layer.

Metadata such as role, experience, skills, location, and application stage helps narrow retrieval to relevant records.

Candidate search

Find Candidates Using Natural-Language Requirements

Recruiters can search using business language instead of manually combining database filters. The system retrieves relevant candidate records based on job requirements, experience, skills, and supporting résumé content.

Evidence-backed candidate summaries

Generate Candidate Summaries Linked to Source Records

The assistant can summarize a candidate’s relevant experience while referencing the résumé, application details, and interviewer notes used to prepare the response.

This helps reviewers verify the summary instead of relying on an unsupported AI recommendation.

Compare candidates for a role

Compare Candidates Against the Same Job Requirements

Candidate Hub can retrieve evidence for multiple candidates and organize it against the selected role. The system assists reviewers by highlighting relevant experience, missing information, and areas requiring further assessment.

The final hiring decision remains with the recruitment team.

Search and compare recruitment records without losing the supporting evidence.

Candidate Hub is designed to assist recruitment teams with information retrieval and review. It does not replace human evaluation or make autonomous hiring decisions.

Business Use:

• Faster candidate research

• Easier résumé and note retrieval

• More consistent candidate comparison

• Evidence-linked summaries

• Reduced repetitive review effort

For further details, watch the entire video below.