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Book a demo (opens in a new tab)For hiring teams meeting the term for the first time: what an AI interviewer does, how a session runs from plan to report, what it should never do, and how to judge one before a pilot.
An AI interviewer is software that holds a live interview with a candidate, asks follow-up questions, and scores the answers against a rubric your team sets. Good ones use the same plan for every candidate, show the evidence behind each score, and leave the hiring decision with people. Most run by voice or video in a browser.
An AI interviewer is a system that conducts a structured job interview in real time, adapts its follow-up questions to what the candidate says, and produces a report that scores each part of the interview against a rubric set before anyone was interviewed, with evidence drawn from the candidate’s own words.
It is different from three tools it is often confused with:
An AI interviewer sits where the first-round screening call used to be: a real conversation, with follow-ups, that ends in a written assessment.
Naira runs a live voice interview, in English, from a link the candidate opens in the browser after confirming their email on the page. Each role has one current interview plan with four to seven rubric dimensions, some of which can be marked must-pass. The seniority of the role picks the modules: two or three of artifact audit, scenario triage, system design and improve the artifact. A candidate’s session copies the plan at the moment they are invited, so edits to the plan reach only new invites, and candidates invited together are measured the same way.
A live interview runs up to 60 minutes, with each module up to 30 and the warm-up, close and candidate questions up to 15 each. A plan that would run longer than 60 minutes is saved as a take-home instead. If the call drops, the candidate comes back into the same interview at the part they were in, with the time they lost added back; that place is held for 24 hours. Technical candidates can read and edit code in an in-browser editor, and their edits are saved with the session; other modules put a document or a code repository on screen, or cast Naira as a counterpart in a role-play.
The reportopens on a recommendations block with the verdict and a summary, an overall score and an alignment level, then a score for each module, and a separate communication section that levels spoken English on the CEFR scale, one level per criterion. Every piece of evidence is tied to a numbered candidate turn and stores the candidate’s exact words; a quote the candidate never said is removed by code, and a rating left with no supported quote is withdrawn. If the grader cannot grade at all, the report says “Not graded — review the transcript” and the decision goes to a person.
A score that cannot be traced to what the candidate said cannot be defended to a hiring manager.
It helps least when the role depends on a relationship built over several conversations, such as a senior executive search. There, use it for structured skill checks, not the whole process.
| Question | What a good answer looks like | What Naira does |
|---|---|---|
| Is the interview two-way? | It asks follow-ups based on the answer. | Follow-ups adapt to each answer; a vague one is asked for an example. |
| Is the rubric fixed per role? | One current plan per role, copied into each session at invite. | One plan per role; a session copies it when the invite is minted. |
| Is every score explained? | Evidence stores the candidate's own words. | Each quote resolves to a numbered candidate turn or is dropped. |
| Who decides? | A person, always. | The report recommends; your team moves the candidate. |
| How do candidates join? | A link, with no app or account. | A link in the browser, with the email confirmed on the page. |
| What if the call drops? | The session resumes where it stopped. | Same interview, same place, lost time added back, for 24 hours. |
| What if it cannot grade? | It says so and hands over to a person. | The report reads not graded and a person reviews the transcript. |
Then run a pilot: take one live role, invite ten candidates, read every report, and ask the hiring manager whether the reports match their own judgement on the candidates they also met. The scoring rubric itself is worth reading first; behavioural anchorsare what make two interviewers’ scores comparable.
Voice keeps the focus on what the candidate says and removes camera anxiety and bandwidth problems. Video adds visual information that most rubrics should not score anyway. For most first-round interviews, voice is enough, and candidates find it easier to take from anywhere. The format decision has its own write-up: voice vs video AI interviews.
An AI interviewer works best after sourcing and outreach and before the hiring manager’s interview. In EmployLabs, Meera finds and scores candidates, Zia reaches them on email, WhatsApp, SMS, calls, X and Reddit, an interested reply leads to an interview invite (sent automatically or after a person approves it), and Naira runs the interview. Nothing runs on its own until a person activates the role.
To go deeper, read what a voice AI interview can measure and how to read an AI interview report.
Every finalist arrives with an interview report that points back to what they actually said.
