Relevant App

Relevant App is an AI transcriber tool. Relevant listens to a podcast while it records, surfacing Reddit, YouTube and news content in a live dashboard, tagging detected topics like people and companies, and (on Pro) saving searchable transcripts of every episode.

Relevant is a production companion for podcasters that works while the microphone is live. As a host records, the app listens to the conversation and pulls matching web material into a dashboard, so background research sits in front of the host instead of in a browser tab. Scrollable feeds refresh continuously with material from Reddit, YouTube and news sources, and the host can glance at them mid-episode when a guest mentions something worth citing. Topic detection is the core mechanic. Specialized algorithms read the conversation and identify named entities such as people, companies and locations. Those topics become filters: one click narrows every feed to a single person or company, which is useful when an episode drifts into a tangent and the host needs context fast. The filter approach also keeps the dashboard from becoming a wall of unrelated links. The tool is aimed at independent podcasters, interview shows and small production teams that record conversations where facts, references and audience questions come up without warning. It suits live or lightly edited formats better than heavily scripted shows, since the value depends on unplanned discussion. Pro subscribers get additional content feeds and can pick any selection of up to three for the dashboard. Pro also unlocks real-time transcription. Recordings are transcribed automatically, transcripts are stored on the account, and they can be retrieved, downloaded, searched or used for fact checking later. Each episode is tagged with its detected topics, so finding the episode where a particular subject came up stops being a memory exercise. Compared with generic meeting transcription services, Relevant is built around the recording session itself: the research feeds and the running topic list are the differentiator, with the searchable transcript archive as the long-term payoff.