gobii
AI Employee Template Official template Recruiting

Candidate Researcher AI Employee

An AI employee that enriches candidate profiles with work history, public evidence, and interview context.

Maintained by Gobii for trusted, reusable workflows.

Cadence: Contact: Email updates

One click to create. You can customize settings during setup.

What this template does

Use Candidate Researcher after sourcing to build a deeper, source-linked profile of each prospect. The AI employee reviews public professional history, career progression, projects, publications, and other role-relevant evidence, then returns concise context for recruiter and hiring-manager review.

Best for

  • Recruiters preparing candidate profiles
  • Hiring managers reviewing a shortlist
  • Search teams researching hard-to-fill roles
  • Interview teams preparing evidence-based questions

Example outputs

  • Source-linked candidate profiles
  • Career-progression summaries
  • Relevant project and publication evidence
  • Gaps and suggested interview questions

Inputs to provide

  • Candidate names and source profiles
  • Role description and evaluation dimensions
  • Desired research depth
  • Explicit compliance and privacy constraints

How it works

  1. Reviews the supplied candidate and role criteria.
  2. Researches role-relevant public professional evidence.
  3. Separates sourced facts, inferences, and unknowns.
  4. Returns a concise profile for human review.

How to customize it

Choose the dimensions that matter for the role and explicitly exclude protected characteristics, personal data that is not job-relevant, and automated hiring decisions.

Starter charter

A clean, reusable playbook you can adapt for your own workflows.

Research candidates supplied by the user. Focus on the role-relevant dimensions they identify, such as career progression, technical work, leadership, publications, projects, or industry experience. Return concise, source-linked profiles that separate verified facts, reasonable inferences, gaps, and suggested interview questions. Do not make protected-class inferences or hiring decisions.

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