@get_ugle

Search inside your video & audio, by meaning, on your machine. Index once. Search forever. No cloud. No credits.

 India
ugle.ai
Joined June 2026
  • Tweets103
  • Following99
  • Followers25
15Media
A newsroom editor rarely starts with a perfect keyword. They start with memory. “The spokesperson explained the budget issue somewhere in the second interview.” “The strongest answer came after we asked about the delay.” “There was a clean soundbite about the announcement.”
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The traditional retrieval process converts that incomplete memory into manual work: open, scrub, listen, skip, rewind and repeat. That is the deadline tax. Ugle’s job is to convert remembered meaning into a timestamped Moment connected to the original source.
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It is not trying to become the editing system. Edit where you already edit. Find what you could not find before. Find the Moment. Then get back to the edit.
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The file is only the container. What professionals actually need is often somewhere inside it. A quote. A scene. An objection. A soundbite. A source. A Moment.
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Ugle makes private audio and video archives searchable by meaning while the underlying media, transcripts and indexes stay on the user’s machine. Find Your Moment.
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A deadline does not care that the interview is 94 minutes long. You remember the answer. What you need is the exact Moment and the source it came from. Search the archive by meaning. Open the timestamp. Keep working.
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Find the soundbite. Pull the clip. Hit the deadline.
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For Ugle, local-first is the architecture, not just a privacy feature. Original audio and video stay on your device, while transcripts and indexes are generated and stored locally, never uploaded to Ugle for processing.
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This protects sensitive content and enables offline search without token costs or cloud-hosted archives. Ugle uses external services for licensing, payments, downloads and updates. Your media, transcripts and indexes remain local. On your machine.
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Ugle has one job: help you retrieve a Moment from media you already own. Your media becomes a Library. The Indexer prepares it locally for search. You use Spotlight to describe what you remember. Ugle finds matching Moments, connected to their original timestamps and sources.
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The experience is search. Transcription and indexing are the infrastructure behind it. What would you search for first?
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The frustrating part is often not knowing whether the material exists. You already know it exists. You remember the conversation, the scene or the soundbite. What you cannot remember is exactly where it happened.
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Ugle is designed to close that gap between remembering the Moment and finding the source. Find Your Moment. What would you search first inside your archive?
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People rarely remember recordings as filenames or exact transcript strings. They remember meaning. “The part where the client was worried about pricing.” “The interview where she explained why the launch was delayed.” “That soundbite about the first customer.”
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Traditional keyword search can struggle when the words you remember are not the words that were actually spoken. ugle.ai indexes transcript segments semantically so Spotlight can search for what a Moment means, not only whether an exact keyword appears.

Ugle | Local-First Media Search

Find the exact moment inside any recording, locally on your machine, with no uploads and no cloud.

ugle.ai
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The useful result is not another generated answer. It is a route back to the original recording and timestamp. Retrieval, not generation. Describe what you remember. Find where it happened. ugle.ai

Ugle | Local-First Media Search

Find the exact moment inside any recording, locally on your machine, with no uploads and no cloud.

ugle.ai
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Why is it easier to search the internet than a video archive sitting on your own computer? For people working with interviews, podcasts, footage and recorded source material, the problem is often not remembering what happened. You remember the quote. You remember the objection. You remember the soundbite. What you don’t remember is which file contains it, where it appears, or the exact timestamp. So the workflow becomes opening files, scrubbing timelines, listening, skipping, rewinding and trying again. Ugle is built around that retrieval gap. It indexes audio and video locally and lets you describe what you remember, so you can return to the relevant Moment in the original source. You spent years building the archive. Finding one moment inside it should not take twenty minutes. #MediaWorkflow #VideoEditing #Journalism
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My live reactions and feedback for ugle.ai: a local-first media search tool. @get_ugle Get your free review: betabloom.app/clarity-consul…
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Ugle retweeted
Ugle@get_ugleAug 7
A folder full of recordings is not the same as a searchable archive. Most media teams already have the files. They have interviews, raw footage, podcast episodes, research calls, lectures, voice notes, source recordings, and old client conversations. ugle.ai
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A search tool is only as useful as the language it can understand. From the beginning, Ugle.ai was built to go beyond English. Its local-first engine supports 90+ languages, using optimised transcription models to extract searchable text directly on your machine. That means you can transcribe an interview in Spanish, analyse a podcast in Japanese, or archive historical footage in Welsh without sending your media to the cloud. Your files stay local. Your content becomes searchable. Your language is no longer a limitation.
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Explore the languages supported by Ugle AI : ugle.ai/blog/languages-suppo…

The 90+ Languages Supported by Ugle

Explore the 90+ languages supported locally by Ugle for fast, on-device audio and video transcription with no cloud required.

ugle.ai
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