Building UniScribe: making audio and video easier to search and reuse

Hey Indie Hackers,

I’m David, founder of UniScribe.

UniScribe is an AI transcription tool that helps people convert audio and video into transcripts, translations, subtitles, and summaries.

I started building it because I kept seeing the same problem: a lot of valuable information is locked inside audio and video. Meetings, interviews, podcasts, lectures, webinars, and YouTube videos often contain useful ideas, but once the content is in spoken format, it becomes hard to search, quote, translate, summarize, or repurpose.

The goal of UniScribe is simple: make spoken content as easy to work with as written content.

Today, users can upload audio or video files, import content from links, generate transcripts, translate them into other languages, create subtitles, identify speakers, and summarize long content with AI.

People use UniScribe for different workflows: creators repurpose videos and podcasts into written content, students and researchers review lectures or interviews, and business users turn meetings and recordings into searchable notes.

I’m still improving the product every week. The main areas I’m focused on now are transcription accuracy, speaker recognition, export workflows, long-form content handling, and making the overall experience simpler.

I’d love to get feedback from other founders here:

Where would transcription or video-to-text fit into your workflow?
And what would make a tool like this genuinely useful enough for you to pay for?