Is a Meeting Transcription Tool Enough to Record and Analyze Interviews?

When an interview ends, you’re left with a recording. These days, meeting note-takers such as Clova Note and Tiro, both popular in Korea, transcribe speech in real time and even summarize it. You already rely on them for meetings, so reaching for one in interviews feels natural. You get a record and a summary, which seems like enough.

But open that interview record a few days later, and something feels missing. It tells you who said what, but it doesn’t tell you whether the candidate should advance or be put on hold.

This article looks at where meeting note-takers help, where they stop, and what interviews need beyond them.

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Why Do We End Up Using Meeting Note-Takers in Interviews?

Using a meeting note-taker for interviews is a natural choice. You’ve already used it in team meetings and client calls, and all you have to do is upload the interview recording to get a transcript and summary. An interview is a conversation too, so it seems you can capture it the same way.

And at first, it really is convenient. You miss less of the conversation because you’re not scrambling to take notes, and you don’t have to listen to the whole thing again afterward. Up to this point, the note-taker does its job.

The problem comes next. Meeting note-takers like Clova Note, Tiro, and Daglo are good at transcribing and summarizing interview recordings, but the record they produce doesn’t tell you whether the candidate should advance or be put on hold. It neatly captures what was said, but it doesn’t judge what those words mean for the hiring decision. These tools were built to document meetings, not to evaluate people.

That is exactly where interviews part ways with meetings. Below, we put meeting note-takers side by side with Interview Pro to show what interviews need beyond a record.

The Misconception That AI Replaces the Interviewer

First, a common misconception worth clearing up. When people hear about using AI in interviews, many picture AI asking candidates questions and even making the hiring call: an avatar on screen running the interview in a human’s place.

Neither meeting note-takers nor Telta Interview Pro work that way. People run the interview. A meeting note-taker turns the conversation into text, and Interview Pro goes a step further and organizes the evidence for evaluation. Neither replaces the interviewer; both take work off the interviewer’s plate.

In short, AI doesn’t evaluate and decide on people. It puts the decisions people make on the same standard.

Interview Pro is designed to start only after the candidate gives prior consent. When the interview ends, the audio recording is discarded rather than stored, and only the text transcript and competency report remain.
Because raw audio never piles up, the burden of handling candidates’ sensitive information is lighter too.

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AI Chat, Meeting Note-Takers, and Telta Interview Pro: What’s the Difference?

The differences become clear when you compare what AI chat, a meeting note-taker, and Interview Pro each leave you with from the same interview conversation.

All three handle transcription and summaries. The differences start right after that. Let’s look at meeting note-takers and AI chat one at a time.

Meeting Note-Takers vs. Telta Interview Pro

A meeting note-taker stops at documenting what was said. Interview Pro goes on to evaluate which competencies those statements demonstrated, and at what level. Given the same interview record, one ends at documentation and the other at evaluation.

That’s why Interview Pro suggests context-aware follow-up questions during the interview, and within an hour of the interview ending it produces a competency report with scores for job-specific and common competencies, plus the candidate statements behind each score. Because every candidate is evaluated against the same standard, you can compare them directly. Meeting note-takers offer neither the evaluation nor the comparison.

In short, a meeting note-taker is a tool for recording, and Interview Pro is a tool for evaluating. Use the note-taker for meetings and Interview Pro for interviews.

AI Chat vs. Telta Interview Pro

Since you can now paste an interview transcript into Claude or ChatGPT and get a summary and even a score, people often ask why they can’t just build their own evaluation tool. Technically, they can. But the hard part of interview evaluation isn’t the model. It’s everything you build on top of it.

The first stumbling block is the standard. Designing which competencies to evaluate and on what scale is the essence of evaluation, but if you write prompts on the fly, the same answer gets a different score every time. When you’re hiring, comparing people and documenting your reasoning, scores that keep shifting are a real problem. Consistent results require a separate process for designing, calibrating, and validating the criteria.

Operations and security also sit outside the model. Real-time transcription and speaker separation during the interview, context-aware question suggestions, and a report delivered within an hour all depend on a supporting system. On top of that, what candidates say is sensitive personal information, so feeding candidate data directly into an external AI tool raises issues such as data processing agreements and consent that have to be addressed.

Put simply, the LLM is the engine. Interview Pro is the tool that adds evaluation criteria, consistency, operations, and security on top of that engine. You could build it yourself, but what hiring evaluation needs isn’t the model itself. It’s validated criteria and reliable operations.

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Where to Start Turning Interview Records Into Evaluations

You can try Interview Pro free for up to five interviews, with no sales inquiry required. There’s no need to change how you interview: get the candidate’s consent and press start. Try it in a real interview and see for yourself what the competency report looks like.

If you want to set up your interview evaluation criteria from scratch, we recommend our article on building an interview scorecard. If you want to dig deeper into why ratings differ from one interviewer to the next, read our article on structured interviews.

Related Reading

• Interviewing in the AI Era: Why Your Scorecard Matters More Than Your Questions
• What Is a Structured Interview? How to Reduce Rating Gaps Between Interviewers

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