AI tools that let recruiters search across interview notes

Which tools can search every interview your team has recorded?

Notta is our recommended starting point for most teams, while Metaview and BrightHire are the dedicated interview-intelligence options for search that must be organised by candidate and role. The table below shows what each pick actually searches, because "search" means three different things depending on the tool.

The scope column matters as much as the features. Notta and Fireflies search across everything you have recorded, which is powerful and keeps the whole archive queryable in one place. Metaview and BrightHire organise search around roles and candidates, which mirrors how recruiters think — the trade-off is a significantly higher price. Neither approach is strictly better: it depends on whether your team needs pipeline structure or a complete, verifiable record of everything said.

Keyword search, AI chat or rediscovery: what's the difference?

Keyword search is the simplest and most trustworthy: you type "Kubernetes" and the tool returns every interview that contains the word, with the moments it appears. Notta's keyword, speaker, date and full-text search works this way, as does Fireflies' global smart search. It is fast and verifiable, but it only finds what you can name.

AI chat lets you ask a question instead of a keyword: "Which finalists for the PM role mentioned Kubernetes?" Notta Brain, Metaview's Assistant, BrightHire's chat assistant, Ashby's AI Candidate Assistant, Otter AI Chat and Fireflies' AskFred all do this. The quality difference is whether the answer shows you where it came from — covered in the next section.

Rediscovery is the recruiting-specific version: "who did we turn down last year who would fit this job?" Metaview's sourcing agent searches past Metaview interviews alongside your ATS profiles and the web from one prompt, and BrightHire's rediscovery agent does the same on its Teams tier. Gem also plays in this space, though we have not verified its interview-search depth. General note takers, including Notta, do not do rediscovery because they do not structure notes by candidate or role — that is a structural difference in how the tools are built, not a gap in their search capability.

Do the answers show where in the interview they came from?

Only some tools do, and you should insist on it. An AI answer that says "the candidate expressed concerns about the compensation band" is close to useless in a hiring decision if you cannot click through to the moment they said it — both for fairness to the candidate and for defending the decision later.

In 2026 manual testing of AI chat tools, Notta, Fathom and tl;dv scored 4 out of 5, meaning "original transcript timestamps and text cited by each answer remain visible." Otter, Fireflies, Read AI, MeetGeek, Fellow and Granola scored 3: "answers do not show the specific original transcript timestamps." Metaview's Assistant is documented to "recall exact moments" about a role or candidate, and Greenhouse Notetaker supports search within a transcript with jumps to timestamps. This testing is not an independent benchmark, so re-check any tool you are serious about in a trial — but if cited answers are a hard requirement for your hiring process, Notta and Metaview are the picks here with the strongest evidence.

How far back can you search?

As far as your retention setting allows — and no further. This is the constraint that quietly ruins archive search: a tool can only answer questions about interviews it still holds.

Greenhouse lets admins keep Notetaker data for up to 60 days, which means a question like "who did we interview last year?" may have no data left to search. Ashby's retention rules default to one year for relevant data types when switched on, and are configurable per data type. Granola's Basic plan keeps 30 days of history. Notta, Metaview, BrightHire and Fireflies do not publish comparable short-term caps in the material we checked, but you should confirm retention defaults in a trial before assuming your archive is permanent. If long-horizon rediscovery is the goal, check the retention policy before the search features — it decides whether there is anything left to find.

Can you search old interviews for a new role?

Yes, with the right tool and the right consent. This is candidate rediscovery: Metaview's sourcing agent searches past Metaview conversations, your ATS profiles and the web from a single prompt, and BrightHire's rediscovery agent surfaces past candidates on the Teams tier. Ashby's AI Candidate Assistant can achieve something similar inside your ATS by drawing on a candidate's stored transcripts, resumes, emails and feedback together.

The privacy point is not optional. Candidates must have been told their interview data may be reused for a different purpose. The UK Information Commissioner's Office audit outcomes on AI in recruitment emphasise purpose limitation and data minimisation — data collected for one hiring process should not silently become a sourcing database for another. Illinois' AI Video Interview Act goes further for video interviews, requiring deletion within 30 days on request when AI analyses the recording. Audio-only interviews fall outside that statute, but the purpose-limitation principle still applies. If rediscovery is on your roadmap, make sure your candidate notices and retention rules were built for it.

Searchable meeting records vs an ATS: what's the difference?

It is worth being precise about what Notta does and does not replace. A tool like Notta records, transcribes and searches your interviews: every conversation becomes a searchable, timestamped document you can query across your whole archive. That is a searchable meeting record, and it solves the "which finalist mentioned Kubernetes?" problem directly.

An ATS solves a different problem: it attaches those records to candidate profiles, pipeline stages and role records, so search is structured by who and which stage rather than by content. Metaview, Ashby and (via integrations) Fireflies operate in that world; Notta does not sync with an ATS or organise notes by candidate or role.

Neither is a substitute for the other. If your team already runs a structured hiring pipeline and needs search to follow it, the ATS-organised tools earn their premium. If your team wants a complete, verifiable, searchable record of every interview at a fraction of the price, Notta is the stronger starting point — and you can always add an ATS-organised tool later if pipeline structure becomes essential.

Can a general note taker do this for a small team?

Often, yes — and Notta is the best-value option among them, which is why it is our overall pick. If your team records a manageable number of interviews and does not need candidate records synced to an ATS, a general note taker with cross-meeting AI chat covers most of the need at a fraction of the price.

Notta Brain analyses multiple meetings and files together, so "which candidates mentioned Kubernetes?" works across a batch of interviews, and Notta's keyword, speaker, date and full-text search handles the rest. At $8.17 a month on the annual Pro plan, it undercuts Fireflies' $10 Pro tier while offering the cited-timestamp answers that Fireflies lacked in 2026 testing. Fireflies counters with listed ATS integrations, which Notta does not offer. Otter's AI Chat also works across meetings at $19.99/user/month on the Business plan, with Greenhouse connectivity via Zapier.

The honest limitation for all three: no candidate or role structure. You are searching content, not a pipeline. For a three-person team doing twenty interviews a month, that is usually a fair trade for the price. Once search needs to power structured hiring decisions across panels and roles, Metaview or BrightHire earn their premium.