Candidate search

Search candidate history in plain language.

Apikuo turns applicant content into searchable embeddings so hiring teams can ask natural-language questions across resumes, notes, analyses, and other candidate documents.

On this page

  • Search with plain-language queries
  • Pull matches from applicant documents, notes, and analyses
  • Keep search scoped to a specific job

Workflow

How search works in Apikuo

  1. 1

    Add applicants and documents to a job in Apikuo.

  2. 2

    Generate embeddings for the candidate set.

  3. 3

    Ask a natural-language question in candidate search.

  4. 4

    Review matched candidates with content previews and AI scores.

Product proof

What the current product supports

Search runs at the job level, not as a generic site-wide keyword search.

Matching content can come from resumes, cover letters, notes, analyses, interview documents, and custom-field text.

Candidate search results can include saved AI analysis scores and interview recommendations.

FAQ

Questions this page should answer clearly.

What can I search across?

Apikuo searches stored candidate content such as resumes, cover letters, notes, analyses, and other indexed applicant content.

Do I need to prepare anything before searching?

Yes. Candidate embeddings need to exist for the job before natural-language search will return semantic matches.

Can search be filtered?

Yes. The search service supports filters for archived status, document types, source types, and score ranges.